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Data Science Tutorial - Random Forest Regression.ipynb
{
"cells": [
{
"metadata": {},
"cell_type": "markdown",
"source": "## Data Science Tutorial - Linear Regression, Random Forest Regressor\n\n\n•\tWhat are the key features behind purchasing a vehicle?\n\n- Correlations\n\n- Transformation Pipline\n\n- Linear Regression Model \n\n- Random Forest Regression\n\n- Cross Validation\n\n- Grid Search - Fine tuning hyperparameters\n\n\nJohn Ryan 15th May 2017"
},
{
"metadata": {},
"cell_type": "markdown",
"source": "### Contents\n\n- Load the data to a pandas data frame\n\n- Correlations between variables\n\n- Missing Value Detection\n\n- Encode Labels\n\n- Cross Validation Train/Test Split\n\n- Creating a Linear Regression Model\n\n- Creating a Random Forest Regressor\n\n- Evaluate Model Performance\n\n- Metric 1: RMSE of correct predictions\n\n- Metric 2: K-fold Cross Validation\n\n- Evaluate Model Performance"
},
{
"metadata": {},
"cell_type": "markdown",
"source": "## What are the key features behind purchasing a vehicle?\n\n"
},
{
"metadata": {},
"cell_type": "markdown",
"source": "#### Read non - tabular data set to a pandas data frame "
},
{
"metadata": {
"collapsed": false,
"trusted": true
},
"cell_type": "code",
"source": "#import the pandas library & define the variable names.\n#Here also tell pandas read_table function to seperate the data at every \"|\" \n#and also assign the variable name to each column. \nimport pandas as pd\nimport numpy as np\nvar_name = [ 'v1','v2','v3','v4','v5','Price','v7','v8','v9','v10','v11','v12','v13','v14','v15',\n 'v16','v17','v18','v19','v20','v21','v22','v23','v24','target']\ndata = pd.read_table('C:\\\\data\\\\SampleData.txt', sep = '|', header = None, names=var_name)\n",
"execution_count": 1,
"outputs": []
},
{
"metadata": {
"collapsed": false,
"trusted": true
},
"cell_type": "code",
"source": "data.head(5)",
"execution_count": 2,
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/html": "<div>\n<table border=\"1\" class=\"dataframe\">\n <thead>\n <tr style=\"text-align: right;\">\n <th></th>\n <th>v1</th>\n <th>v2</th>\n <th>v3</th>\n <th>v4</th>\n <th>v5</th>\n <th>Price</th>\n <th>v7</th>\n <th>v8</th>\n <th>v9</th>\n <th>v10</th>\n <th>...</th>\n <th>v16</th>\n <th>v17</th>\n <th>v18</th>\n <th>v19</th>\n <th>v20</th>\n <th>v21</th>\n <th>v22</th>\n <th>v23</th>\n <th>v24</th>\n <th>target</th>\n </tr>\n </thead>\n <tbody>\n <tr>\n <th>0</th>\n <td>102120401529162609</td>\n <td>1001396153</td>\n <td>2017-01-02 12:04:01</td>\n <td>2</td>\n <td>1</td>\n <td>750.26</td>\n <td>2</td>\n <td>1</td>\n <td>1</td>\n <td>5</td>\n <td>...</td>\n <td>8.0</td>\n <td>385</td>\n <td>3</td>\n <td>1</td>\n <td>1</td>\n <td>2</td>\n <td>14.0</td>\n <td>2017-02-04 00:00:00</td>\n <td>71</td>\n <td>0</td>\n </tr>\n <tr>\n <th>1</th>\n <td>102120401529162609</td>\n <td>401793302</td>\n <td>2017-01-02 12:04:01</td>\n <td>2</td>\n <td>1</td>\n <td>322.12</td>\n <td>4</td>\n <td>1</td>\n <td>1</td>\n <td>5</td>\n <td>...</td>\n <td>6.0</td>\n <td>1368</td>\n <td>3</td>\n <td>0</td>\n <td>1</td>\n <td>2</td>\n <td>14.0</td>\n <td>2017-02-04 00:00:00</td>\n <td>71</td>\n <td>0</td>\n </tr>\n <tr>\n <th>2</th>\n <td>102120401529162609</td>\n <td>2100312948</td>\n <td>2017-01-02 12:04:01</td>\n <td>1</td>\n <td>1</td>\n <td>466.38</td>\n <td>1</td>\n <td>1</td>\n <td>2</td>\n <td>5</td>\n <td>...</td>\n <td>7.0</td>\n <td>1741</td>\n <td>3</td>\n <td>0</td>\n <td>1</td>\n <td>2</td>\n <td>14.0</td>\n <td>2017-02-04 00:00:00</td>\n <td>71</td>\n <td>0</td>\n </tr>\n <tr>\n <th>3</th>\n <td>102120401529162609</td>\n <td>1697088827</td>\n <td>2017-01-02 12:04:01</td>\n <td>1</td>\n <td>1</td>\n <td>303.52</td>\n <td>4</td>\n <td>1</td>\n <td>2</td>\n <td>5</td>\n <td>...</td>\n <td>6.0</td>\n <td>1912</td>\n <td>3</td>\n <td>0</td>\n <td>1</td>\n <td>2</td>\n <td>14.0</td>\n <td>2017-02-04 00:00:00</td>\n <td>71</td>\n <td>0</td>\n </tr>\n <tr>\n <th>4</th>\n <td>102120401529162609</td>\n <td>682137395</td>\n <td>2017-01-02 12:04:01</td>\n <td>1</td>\n <td>1</td>\n <td>282.19</td>\n <td>1</td>\n <td>1</td>\n <td>1</td>\n <td>3</td>\n <td>...</td>\n <td>6.0</td>\n <td>1960</td>\n <td>3</td>\n <td>0</td>\n <td>1</td>\n <td>2</td>\n <td>14.0</td>\n <td>2017-02-04 00:00:00</td>\n <td>71</td>\n <td>0</td>\n </tr>\n </tbody>\n</table>\n<p>5 rows × 25 columns</p>\n</div>",
"text/plain": " v1 v2 v3 v4 v5 Price v7 \\\n0 102120401529162609 1001396153 2017-01-02 12:04:01 2 1 750.26 2 \n1 102120401529162609 401793302 2017-01-02 12:04:01 2 1 322.12 4 \n2 102120401529162609 2100312948 2017-01-02 12:04:01 1 1 466.38 1 \n3 102120401529162609 1697088827 2017-01-02 12:04:01 1 1 303.52 4 \n4 102120401529162609 682137395 2017-01-02 12:04:01 1 1 282.19 1 \n\n v8 v9 v10 ... v16 v17 v18 v19 v20 v21 v22 \\\n0 1 1 5 ... 8.0 385 3 1 1 2 14.0 \n1 1 1 5 ... 6.0 1368 3 0 1 2 14.0 \n2 1 2 5 ... 7.0 1741 3 0 1 2 14.0 \n3 1 2 5 ... 6.0 1912 3 0 1 2 14.0 \n4 1 1 3 ... 6.0 1960 3 0 1 2 14.0 \n\n v23 v24 target \n0 2017-02-04 00:00:00 71 0 \n1 2017-02-04 00:00:00 71 0 \n2 2017-02-04 00:00:00 71 0 \n3 2017-02-04 00:00:00 71 0 \n4 2017-02-04 00:00:00 71 0 \n\n[5 rows x 25 columns]"
},
"metadata": {},
"execution_count": 2
}
]
},
{
"metadata": {
"collapsed": false,
"trusted": true
},
"cell_type": "code",
"source": "data.describe()",
"execution_count": 3,
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/html": "<div>\n<table border=\"1\" class=\"dataframe\">\n <thead>\n <tr style=\"text-align: right;\">\n <th></th>\n <th>v1</th>\n <th>v2</th>\n <th>v4</th>\n <th>v5</th>\n <th>Price</th>\n <th>v7</th>\n <th>v8</th>\n <th>v9</th>\n <th>v10</th>\n <th>v11</th>\n <th>...</th>\n <th>v15</th>\n <th>v16</th>\n <th>v17</th>\n <th>v18</th>\n <th>v19</th>\n <th>v20</th>\n <th>v21</th>\n <th>v22</th>\n <th>v24</th>\n <th>target</th>\n </tr>\n </thead>\n <tbody>\n <tr>\n <th>count</th>\n <td>1.108765e+06</td>\n <td>1.108765e+06</td>\n <td>1.108765e+06</td>\n <td>1.108765e+06</td>\n <td>1.108765e+06</td>\n <td>1.108765e+06</td>\n <td>1.108765e+06</td>\n <td>1.108765e+06</td>\n <td>1.108765e+06</td>\n <td>1.108765e+06</td>\n <td>...</td>\n <td>1.108765e+06</td>\n <td>1.095568e+06</td>\n <td>1.108765e+06</td>\n <td>1.108765e+06</td>\n <td>1.108765e+06</td>\n <td>1.108765e+06</td>\n <td>1.108765e+06</td>\n <td>1.108765e+06</td>\n <td>1.108765e+06</td>\n <td>1.108765e+06</td>\n </tr>\n <tr>\n <th>mean</th>\n <td>2.881691e+16</td>\n <td>1.072195e+09</td>\n <td>1.265895e+00</td>\n <td>9.341276e-01</td>\n <td>6.278993e+02</td>\n <td>2.542878e+00</td>\n <td>2.574618e+00</td>\n <td>1.305501e+00</td>\n <td>4.531986e+00</td>\n <td>2.841257e+00</td>\n <td>...</td>\n <td>4.596040e+00</td>\n <td>6.827730e+00</td>\n <td>1.651687e+03</td>\n <td>3.537109e+00</td>\n <td>2.225611e-01</td>\n <td>2.446152e+00</td>\n <td>1.624372e+00</td>\n <td>9.322821e+00</td>\n <td>9.803950e+02</td>\n <td>3.659928e-03</td>\n </tr>\n <tr>\n <th>std</th>\n <td>4.649240e+16</td>\n <td>6.231840e+08</td>\n <td>4.993720e-01</td>\n <td>2.480590e-01</td>\n <td>6.351999e+02</td>\n <td>2.435445e+00</td>\n <td>2.869880e+00</td>\n <td>7.680090e-01</td>\n <td>8.189798e-01</td>\n <td>1.432739e+00</td>\n <td>...</td>\n <td>3.136224e+00</td>\n <td>8.699843e-01</td>\n <td>9.968389e+02</td>\n <td>2.447612e+00</td>\n <td>4.159661e-01</td>\n <td>3.541486e+00</td>\n <td>4.842848e-01</td>\n <td>5.445166e+00</td>\n <td>1.172454e+03</td>\n <td>6.038656e-02</td>\n </tr>\n <tr>\n <th>min</th>\n <td>3.114840e+14</td>\n <td>3.918000e+03</td>\n <td>1.000000e+00</td>\n <td>0.000000e+00</td>\n <td>1.591800e+02</td>\n <td>0.000000e+00</td>\n <td>1.000000e+00</td>\n <td>1.000000e+00</td>\n <td>2.000000e+00</td>\n <td>0.000000e+00</td>\n <td>...</td>\n <td>1.000000e+00</td>\n <td>4.000000e+00</td>\n <td>4.700000e+01</td>\n <td>2.000000e+00</td>\n <td>0.000000e+00</td>\n <td>1.000000e+00</td>\n <td>1.000000e+00</td>\n <td>1.000000e+00</td>\n <td>7.100000e+01</td>\n <td>0.000000e+00</td>\n </tr>\n <tr>\n <th>25%</th>\n <td>5.214847e+14</td>\n <td>5.275361e+08</td>\n <td>1.000000e+00</td>\n <td>1.000000e+00</td>\n <td>2.942000e+02</td>\n <td>1.000000e+00</td>\n <td>1.000000e+00</td>\n <td>1.000000e+00</td>\n <td>4.000000e+00</td>\n <td>2.000000e+00</td>\n <td>...</td>\n <td>2.000000e+00</td>\n <td>6.000000e+00</td>\n <td>4.790000e+02</td>\n <td>3.000000e+00</td>\n <td>0.000000e+00</td>\n <td>1.000000e+00</td>\n <td>1.000000e+00</td>\n <td>6.000000e+00</td>\n <td>7.100000e+01</td>\n <td>0.000000e+00</td>\n </tr>\n <tr>\n <th>50%</th>\n <td>8.114858e+14</td>\n <td>1.072732e+09</td>\n <td>1.000000e+00</td>\n <td>1.000000e+00</td>\n <td>4.364200e+02</td>\n <td>1.000000e+00</td>\n <td>1.000000e+00</td>\n <td>1.000000e+00</td>\n <td>5.000000e+00</td>\n <td>3.000000e+00</td>\n <td>...</td>\n <td>4.000000e+00</td>\n <td>7.000000e+00</td>\n <td>1.912000e+03</td>\n <td>3.000000e+00</td>\n <td>0.000000e+00</td>\n <td>1.000000e+00</td>\n <td>2.000000e+00</td>\n <td>7.000000e+00</td>\n <td>7.100000e+01</td>\n <td>0.000000e+00</td>\n </tr>\n <tr>\n <th>75%</th>\n <td>1.021232e+17</td>\n <td>1.619128e+09</td>\n <td>1.000000e+00</td>\n <td>1.000000e+00</td>\n <td>7.245900e+02</td>\n <td>4.000000e+00</td>\n <td>1.000000e+00</td>\n <td>1.000000e+00</td>\n <td>5.000000e+00</td>\n <td>4.000000e+00</td>\n <td>...</td>\n <td>7.000000e+00</td>\n <td>8.000000e+00</td>\n <td>2.375000e+03</td>\n <td>3.000000e+00</td>\n <td>0.000000e+00</td>\n <td>2.000000e+00</td>\n <td>2.000000e+00</td>\n <td>1.300000e+01</td>\n <td>2.492000e+03</td>\n <td>0.000000e+00</td>\n </tr>\n <tr>\n <th>max</th>\n <td>1.091055e+17</td>\n <td>2.147477e+09</td>\n <td>3.000000e+00</td>\n <td>1.000000e+00</td>\n <td>3.687822e+04</td>\n <td>1.100000e+01</td>\n <td>9.000000e+00</td>\n <td>5.000000e+00</td>\n <td>5.000000e+00</td>\n <td>6.000000e+00</td>\n <td>...</td>\n <td>1.600000e+01</td>\n <td>8.000000e+00</td>\n <td>6.021000e+03</td>\n <td>1.700000e+01</td>\n <td>1.000000e+00</td>\n <td>4.600000e+01</td>\n <td>2.000000e+00</td>\n <td>7.000000e+01</td>\n <td>2.492000e+03</td>\n <td>1.000000e+00</td>\n </tr>\n </tbody>\n</table>\n<p>8 rows × 23 columns</p>\n</div>",
"text/plain": " v1 v2 v4 v5 Price \\\ncount 1.108765e+06 1.108765e+06 1.108765e+06 1.108765e+06 1.108765e+06 \nmean 2.881691e+16 1.072195e+09 1.265895e+00 9.341276e-01 6.278993e+02 \nstd 4.649240e+16 6.231840e+08 4.993720e-01 2.480590e-01 6.351999e+02 \nmin 3.114840e+14 3.918000e+03 1.000000e+00 0.000000e+00 1.591800e+02 \n25% 5.214847e+14 5.275361e+08 1.000000e+00 1.000000e+00 2.942000e+02 \n50% 8.114858e+14 1.072732e+09 1.000000e+00 1.000000e+00 4.364200e+02 \n75% 1.021232e+17 1.619128e+09 1.000000e+00 1.000000e+00 7.245900e+02 \nmax 1.091055e+17 2.147477e+09 3.000000e+00 1.000000e+00 3.687822e+04 \n\n v7 v8 v9 v10 v11 \\\ncount 1.108765e+06 1.108765e+06 1.108765e+06 1.108765e+06 1.108765e+06 \nmean 2.542878e+00 2.574618e+00 1.305501e+00 4.531986e+00 2.841257e+00 \nstd 2.435445e+00 2.869880e+00 7.680090e-01 8.189798e-01 1.432739e+00 \nmin 0.000000e+00 1.000000e+00 1.000000e+00 2.000000e+00 0.000000e+00 \n25% 1.000000e+00 1.000000e+00 1.000000e+00 4.000000e+00 2.000000e+00 \n50% 1.000000e+00 1.000000e+00 1.000000e+00 5.000000e+00 3.000000e+00 \n75% 4.000000e+00 1.000000e+00 1.000000e+00 5.000000e+00 4.000000e+00 \nmax 1.100000e+01 9.000000e+00 5.000000e+00 5.000000e+00 6.000000e+00 \n\n ... v15 v16 v17 v18 \\\ncount ... 1.108765e+06 1.095568e+06 1.108765e+06 1.108765e+06 \nmean ... 4.596040e+00 6.827730e+00 1.651687e+03 3.537109e+00 \nstd ... 3.136224e+00 8.699843e-01 9.968389e+02 2.447612e+00 \nmin ... 1.000000e+00 4.000000e+00 4.700000e+01 2.000000e+00 \n25% ... 2.000000e+00 6.000000e+00 4.790000e+02 3.000000e+00 \n50% ... 4.000000e+00 7.000000e+00 1.912000e+03 3.000000e+00 \n75% ... 7.000000e+00 8.000000e+00 2.375000e+03 3.000000e+00 \nmax ... 1.600000e+01 8.000000e+00 6.021000e+03 1.700000e+01 \n\n v19 v20 v21 v22 v24 \\\ncount 1.108765e+06 1.108765e+06 1.108765e+06 1.108765e+06 1.108765e+06 \nmean 2.225611e-01 2.446152e+00 1.624372e+00 9.322821e+00 9.803950e+02 \nstd 4.159661e-01 3.541486e+00 4.842848e-01 5.445166e+00 1.172454e+03 \nmin 0.000000e+00 1.000000e+00 1.000000e+00 1.000000e+00 7.100000e+01 \n25% 0.000000e+00 1.000000e+00 1.000000e+00 6.000000e+00 7.100000e+01 \n50% 0.000000e+00 1.000000e+00 2.000000e+00 7.000000e+00 7.100000e+01 \n75% 0.000000e+00 2.000000e+00 2.000000e+00 1.300000e+01 2.492000e+03 \nmax 1.000000e+00 4.600000e+01 2.000000e+00 7.000000e+01 2.492000e+03 \n\n target \ncount 1.108765e+06 \nmean 3.659928e-03 \nstd 6.038656e-02 \nmin 0.000000e+00 \n25% 0.000000e+00 \n50% 0.000000e+00 \n75% 0.000000e+00 \nmax 1.000000e+00 \n\n[8 rows x 23 columns]"
},
"metadata": {},
"execution_count": 3
}
]
},
{
"metadata": {
"collapsed": false,
"trusted": true
},
"cell_type": "code",
"source": "import matplotlib.pyplot as plt\n%matplotlib inline\n#data.hist(bins=50, figsize=(20,15))\n#plt.show()",
"execution_count": 4,
"outputs": []
},
{
"metadata": {},
"cell_type": "markdown",
"source": "### Distribution of the Price Variable\n\nLooking at the distribution below we see a clear right skewed despersion.It looks like from the horizontal axis on the histogram that over 900,000 vechicle prices are between the value of 0 - 1000. This distribution is not ideal for regression but will be usfeul when fitting the regression model. "
},
{
"metadata": {
"collapsed": false,
"trusted": true
},
"cell_type": "code",
"source": "#Limit Balance Histogram\ndata['Price'].hist(bins = 50)\nplt.show()",
"execution_count": 5,
"outputs": [
{
"output_type": "display_data",
"data": {
"image/png": 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"text/plain": "<matplotlib.figure.Figure at 0x1175b4e0>"
},
"metadata": {}
}
]
},
{
"metadata": {},
"cell_type": "markdown",
"source": "#### 2.1 Logging Price to Improve distribution"
},
{
"metadata": {
"collapsed": false,
"trusted": true
},
"cell_type": "code",
"source": "#import numpy library for the computation of np.log and create resulting histogram\nimport numpy as np\ndata['price_log'] = np.log(data['Price'])\ndata['price_log'].hist(bins=20)",
"execution_count": 6,
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/plain": "<matplotlib.axes._subplots.AxesSubplot at 0x11659c50>"
},
"metadata": {},
"execution_count": 6
},
{
"output_type": "display_data",
"data": {
"image/png": 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"text/plain": "<matplotlib.figure.Figure at 0x184200f0>"
},
"metadata": {}
}
]
},
{
"metadata": {},
"cell_type": "markdown",
"source": "### 3. Looking for Correlations and meaure of ‘association’\n\nFinding the relationship between two quantitative variables without being able to infer causal relationships, it is simply a number indicating how a number of relationships between variables closely follows a straight line. Correlation is a statistical technique used to determine the degree to which two variables are related.\n\nBefore we carry out a simple linear regression between a number of variables we need to see if they are related.\n\nCorrelation coefficient is also known as Pearson Product-Moment Correlation Coefficient (r). \n\nWhile in regression the emphasis is on predicting one variable from the other, in correlation the emphasis is on the degree to which a linear model may describe the relationship between variables.\n\nThe value of r ranges between ( -1) and ( +1) The value of r denotes the strength of the association we can see from the correlation matrix below that the duration v22,v15,v19 and v14 have the highest correlations. How ever we see that v22(Rental Duration)has the highest positive relationship with a value of 0.423 which is not overly strong a value over 0.75 however would offer more confidence.\n\nWhen interpreting the scatterplot it was important to look for trends in the data as you go from left to right:\n\nThe data shows a central uphill pattern as you move from left to right, which indicates some positive relationship between v22(Rental Duration) and v6 (price of the car).In theory as each of the X values (v22,v15,v19,v14)increase i.e (moves right), so to will the price increase (moves upwards)."
},
{
"metadata": {},
"cell_type": "markdown",
"source": "##### Scatter Plot 1 - Price(v6) vs Feature(v22)"
},
{
"metadata": {
"collapsed": false,
"trusted": true
},
"cell_type": "code",
"source": "#Plot Price vs Feature(v22)\ndata.plot(kind='scatter', x='v22', y='Price', alpha = 0.1) ",
"execution_count": 7,
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/plain": "<matplotlib.axes._subplots.AxesSubplot at 0x1566a7b8>"
},
"metadata": {},
"execution_count": 7
},
{
"output_type": "display_data",
"data": {
"image/png": 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Kf7Y5GXMFoPmsEXa1zp9DCtc1UMpmZCRDbe2NU/NeurpG6O19jtHRKkwzQ2dn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+JKgRvGqwqbB2MYeUJEGoFJVd0rIvOBJ4Fl6tLQbFBfsVVEfgA8qqr/kU95DeNUsR6MYeQAEfkn\nEbkhY/l24J2quheO5e3qAub65d9kbP4ELk+dYbyqMANjGLnhh7jCdoH3+3UA+MJliWBwMtbHgQ8C\nmQbHMF4VnFXZlA1jpqKq20Rkrs9CWwP0quoBAD889j2cITmRb+KGxx7PnbSGcWYwA2MYueNHwNW4\naoA/BBCRcuCXwGfUFS87hoh8Dpijqh/LtaCGcSYwA2MYueMB4G5gNvAmX2TqQeC7qvpg5g99Bci3\nAW/OuZSGcYawKDLDyCEish3oUtUrfZXAb+NqkgiuQuBHVHW7iKSBF4BQxfOnqvqFPIltGKeFGRjD\nMAwjK1gUmWEYhpEVzMAYhmEYWcEMjGEYhpEVzMAYhmEYWcEMjGEYhpEVzMAYhmEYWcEMjGEYhpEV\nzMAYhmEYWeH/AWYImNBy2bG+AAAAAElFTkSuQmCC\n",
"text/plain": "<matplotlib.figure.Figure at 0x1842b4e0>"
},
"metadata": {}
}
]
},
{
"metadata": {},
"cell_type": "markdown",
"source": "##### Scatter Plot 2 - Price(v6) vs Feature(v22) group by Purchase\n\nFrom the simple plot below we can clearly see that as the rental duration increases the number of booking decline. However we see a higher cluster of bookings between short rental durations of 10 & 20 but a sudden sharp increase in prices between 20 & 30 leading to a period of decline in purchases.It may be appropriate to suggest that by decreasing or normalising the car rental price to between 10,000 and 15,000 for the rental periods between 20 & 30 may lead to an increased volume of bookings.\n\n1 = Car booking \n\n0= No car booking"
},
{
"metadata": {
"collapsed": false,
"trusted": true
},
"cell_type": "code",
"source": "import seaborn as sns\nsns.set_style('whitegrid')\nsns.FacetGrid(data, hue=\"target\", size=5) \\\n .map(plt.scatter, \"v22\", \"Price\") \\\n .add_legend();",
"execution_count": 8,
"outputs": [
{
"output_type": "display_data",
"data": {
"image/png": 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581m6dCkDBgzg/vvv5/HHH0dRFNauXctLL73k1o/QHd5qJN6Ul5eHpLyukLL7VtmRLl/K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\n",
"text/plain": "<matplotlib.figure.Figure at 0x17616198>"
},
"metadata": {}
}
]
},
{
"metadata": {
"collapsed": false,
"trusted": true
},
"cell_type": "code",
"source": "sns.regplot(x= \"v22\", y=\"Price\", data=data)",
"execution_count": 9,
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/plain": "<matplotlib.axes._subplots.AxesSubplot at 0x18c0e630>"
},
"metadata": {},
"execution_count": 9
},
{
"output_type": "display_data",
"data": {
"image/png": 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fFOZMTaem3q7XMZgzNd3wvEB37ayobfXb7mGUcPraL3J58Pmdes7Ca7/I5c/v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\nQmL6/0G3OZ2mqJiCAAAAAElFTkSuQmCC\n",
"text/plain": "<matplotlib.figure.Figure at 0x14cbcd68>"
},
"metadata": {}
}
]
},
{
"metadata": {
"collapsed": false,
"trusted": true
},
"cell_type": "code",
"source": "sns.lmplot(x= \"v22\", y=\"Price\", data=data)",
"execution_count": 10,
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/plain": "<seaborn.axisgrid.FacetGrid at 0x18458390>"
},
"metadata": {},
"execution_count": 10
},
{
"output_type": "display_data",
"data": {
"image/png": 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PTnTQ7qobHxeEqgy9TfhFNX/8LfuT51qZOjmDlGQjigIL7ri+ak8I1x5Diq7R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\nliREMDRxE72gKKMXSqJGUb6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wIHu/G8uXNGMy6Jk9I5uWdivdvQN/o1xzwpD1NfyZOiWd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\nvGUaWikpGTpzL1KcLg9Xuvpo7eylrcP7/9bOXto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"text/plain": "<matplotlib.figure.Figure at 0x18458240>"
},
"metadata": {}
}
]
},
{
"metadata": {},
"cell_type": "markdown",
"source": "### Visualizing the correlation matrix "
},
{
"metadata": {
"collapsed": false,
"trusted": true
},
"cell_type": "code",
"source": "#Plot a correlation matrix \nfrom biokit.viz import corrplot\nc = corrplot.Corrplot(data)\nc.plot()",
"execution_count": 11,
"outputs": [
{
"output_type": "stream",
"text": "Computing correlation\n",
"name": "stdout"
},
{
"output_type": "display_data",
"data": {
"image/png": 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mZ4fJM2fC2tpa7zVIunwZ5QUF6CIQwNrSEmVVVRARAjcPD/iPGUPVu70u7uJF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w0J2YSurnaLccXF+cjMNDQxP3PmjBWdJ7B+/VqMjAxb/L379+9izx5dSY6joyMn/F1nZwd8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\n",
"text/plain": "<matplotlib.figure.Figure at 0x17ee42e8>"
},
"metadata": {}
}
]
},
{
"metadata": {
"collapsed": true,
"trusted": true
},
"cell_type": "code",
"source": "corr_matrix = data.corr()",
"execution_count": 12,
"outputs": []
},
{
"metadata": {
"collapsed": false,
"trusted": true
},
"cell_type": "code",
"source": "corr_matrix[\"Price\"].sort_values(ascending=False)",
"execution_count": 13,
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/plain": "Price 1.000000\nprice_log 0.841488\nv22 0.423331\nv15 0.398544\nv19 0.390827\nv14 0.221968\nv16 0.195748\nv11 0.176109\nv12 0.169756\nv21 0.100535\nv4 0.093966\nv17 0.086594\nv5 0.085926\nv7 0.050325\nv13 0.041645\nv9 0.040714\nv18 0.018612\nv20 0.013213\nv2 0.003210\nv1 -0.002696\nv10 -0.027845\ntarget -0.028054\nv8 -0.075665\nv24 -0.100535\nName: Price, dtype: float64"
},
"metadata": {},
"execution_count": 13
}
]
},
{
"metadata": {},
"cell_type": "markdown",
"source": "### We select the top most correlated features and input to Regression Model"
},
{
"metadata": {
"collapsed": false,
"trusted": true
},
"cell_type": "code",
"source": "#create a new dataframe with highly correlated features\nx = pd.DataFrame(data, columns = ['Price','v22','v15','v19','v14','v16','v12'])\nx.tail(4)",
"execution_count": 14,
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/html": "<div>\n<table border=\"1\" class=\"dataframe\">\n <thead>\n <tr style=\"text-align: right;\">\n <th></th>\n <th>Price</th>\n <th>v22</th>\n <th>v15</th>\n <th>v19</th>\n <th>v14</th>\n <th>v16</th>\n <th>v12</th>\n </tr>\n </thead>\n <tbody>\n <tr>\n <th>1108761</th>\n <td>643.88</td>\n <td>4.0</td>\n <td>8</td>\n <td>0</td>\n <td>0</td>\n <td>7.0</td>\n <td>7</td>\n </tr>\n <tr>\n <th>1108762</th>\n <td>201.83</td>\n <td>4.0</td>\n <td>2</td>\n <td>0</td>\n <td>0</td>\n <td>6.0</td>\n <td>5</td>\n </tr>\n <tr>\n <th>1108763</th>\n <td>465.06</td>\n <td>4.0</td>\n <td>7</td>\n <td>0</td>\n <td>1</td>\n <td>8.0</td>\n <td>5</td>\n </tr>\n <tr>\n <th>1108764</th>\n <td>318.97</td>\n <td>4.0</td>\n <td>8</td>\n <td>0</td>\n <td>0</td>\n <td>7.0</td>\n <td>7</td>\n </tr>\n </tbody>\n</table>\n</div>",
"text/plain": " Price v22 v15 v19 v14 v16 v12\n1108761 643.88 4.0 8 0 0 7.0 7\n1108762 201.83 4.0 2 0 0 6.0 5\n1108763 465.06 4.0 7 0 1 8.0 5\n1108764 318.97 4.0 8 0 0 7.0 7"
},
"metadata": {},
"execution_count": 14
}
]
},
{
"metadata": {},
"cell_type": "markdown",
"source": "### 4. Missing Value Detection"
},
{
"metadata": {
"collapsed": false,
"trusted": true
},
"cell_type": "code",
"source": "#check for missing values in the dataframe\nx.apply(lambda x: sum(x.isnull()),axis=0)",
"execution_count": 15,
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/plain": "Price 0\nv22 0\nv15 0\nv19 0\nv14 0\nv16 13197\nv12 0\ndtype: int64"
},
"metadata": {},
"execution_count": 15
}
]
},
{
"metadata": {
"collapsed": false,
"trusted": true
},
"cell_type": "code",
"source": "#Missing Value imputation using median value;\nx = x.fillna(x.median())\nx.head(7)",
"execution_count": 16,
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/html": "<div>\n<table border=\"1\" class=\"dataframe\">\n <thead>\n <tr style=\"text-align: right;\">\n <th></th>\n <th>Price</th>\n <th>v22</th>\n <th>v15</th>\n <th>v19</th>\n <th>v14</th>\n <th>v16</th>\n <th>v12</th>\n </tr>\n </thead>\n <tbody>\n <tr>\n <th>0</th>\n <td>750.26</td>\n <td>14.0</td>\n <td>8</td>\n <td>1</td>\n <td>0</td>\n <td>8.0</td>\n <td>7</td>\n </tr>\n <tr>\n <th>1</th>\n <td>322.12</td>\n <td>14.0</td>\n <td>4</td>\n <td>0</td>\n <td>0</td>\n <td>6.0</td>\n <td>5</td>\n </tr>\n <tr>\n <th>2</th>\n <td>466.38</td>\n <td>14.0</td>\n <td>4</td>\n <td>0</td>\n <td>0</td>\n <td>7.0</td>\n <td>5</td>\n </tr>\n <tr>\n <th>3</th>\n <td>303.52</td>\n <td>14.0</td>\n <td>4</td>\n <td>0</td>\n <td>0</td>\n <td>6.0</td>\n <td>5</td>\n </tr>\n <tr>\n <th>4</th>\n <td>282.19</td>\n <td>14.0</td>\n <td>2</td>\n <td>0</td>\n <td>0</td>\n <td>6.0</td>\n <td>4</td>\n </tr>\n <tr>\n <th>5</th>\n <td>318.60</td>\n <td>14.0</td>\n <td>1</td>\n <td>0</td>\n <td>0</td>\n <td>7.0</td>\n <td>4</td>\n </tr>\n <tr>\n <th>6</th>\n <td>334.61</td>\n <td>14.0</td>\n <td>2</td>\n <td>0</td>\n <td>0</td>\n <td>8.0</td>\n <td>5</td>\n </tr>\n </tbody>\n</table>\n</div>",
"text/plain": " Price v22 v15 v19 v14 v16 v12\n0 750.26 14.0 8 1 0 8.0 7\n1 322.12 14.0 4 0 0 6.0 5\n2 466.38 14.0 4 0 0 7.0 5\n3 303.52 14.0 4 0 0 6.0 5\n4 282.19 14.0 2 0 0 6.0 4\n5 318.60 14.0 1 0 0 7.0 4\n6 334.61 14.0 2 0 0 8.0 5"
},
"metadata": {},
"execution_count": 16
}
]
},
{
"metadata": {},
"cell_type": "markdown",
"source": "### 5. One Hot Label Encoder"
},
{
"metadata": {
"collapsed": false,
"trusted": true
},
"cell_type": "code",
"source": "#Label encoder\nfrom sklearn.preprocessing import LabelEncoder\n\nfor feature in x.columns:\n if x[feature].dtype=='object':\n le = LabelEncoder()\n x[feature] = le.fit_transform(x[feature])\nx.tail(5)",
"execution_count": 17,
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/html": "<div>\n<table border=\"1\" class=\"dataframe\">\n <thead>\n <tr style=\"text-align: right;\">\n <th></th>\n <th>Price</th>\n <th>v22</th>\n <th>v15</th>\n <th>v19</th>\n <th>v14</th>\n <th>v16</th>\n <th>v12</th>\n </tr>\n </thead>\n <tbody>\n <tr>\n <th>1108760</th>\n <td>633.72</td>\n <td>4.0</td>\n <td>7</td>\n <td>0</td>\n <td>0</td>\n <td>8.0</td>\n <td>5</td>\n </tr>\n <tr>\n <th>1108761</th>\n <td>643.88</td>\n <td>4.0</td>\n <td>8</td>\n <td>0</td>\n <td>0</td>\n <td>7.0</td>\n <td>7</td>\n </tr>\n <tr>\n <th>1108762</th>\n <td>201.83</td>\n <td>4.0</td>\n <td>2</td>\n <td>0</td>\n <td>0</td>\n <td>6.0</td>\n <td>5</td>\n </tr>\n <tr>\n <th>1108763</th>\n <td>465.06</td>\n <td>4.0</td>\n <td>7</td>\n <td>0</td>\n <td>1</td>\n <td>8.0</td>\n <td>5</td>\n </tr>\n <tr>\n <th>1108764</th>\n <td>318.97</td>\n <td>4.0</td>\n <td>8</td>\n <td>0</td>\n <td>0</td>\n <td>7.0</td>\n <td>7</td>\n </tr>\n </tbody>\n</table>\n</div>",
"text/plain": " Price v22 v15 v19 v14 v16 v12\n1108760 633.72 4.0 7 0 0 8.0 5\n1108761 643.88 4.0 8 0 0 7.0 7\n1108762 201.83 4.0 2 0 0 6.0 5\n1108763 465.06 4.0 7 0 1 8.0 5\n1108764 318.97 4.0 8 0 0 7.0 7"
},
"metadata": {},
"execution_count": 17
}
]
},
{
"metadata": {
"collapsed": true
},
"cell_type": "markdown",
"source": "### 6. Feature Scaling - Normalization with Standard Scaling"
},
{
"metadata": {
"collapsed": false,
"trusted": true
},
"cell_type": "code",
"source": "from sklearn import preprocessing\n#scale the data \nfrom sklearn.preprocessing import StandardScaler\nscaler = preprocessing.StandardScaler().fit(x)\nX = scaler.transform(x)\nY = x.Price.values\nprint (X)",
"execution_count": 18,
"outputs": [
{
"output_type": "stream",
"text": "[[ 0.19263346 0.85896011 1.0853695 ..., -0.4569599 1.35286693\n 1.59963548]\n [-0.48139084 0.85896011 -0.19005021 ..., -0.4569599 -0.95929131\n -0.19347275]\n [-0.25428115 0.85896011 -0.19005021 ..., -0.4569599 0.19678781\n -0.19347275]\n ..., \n [-0.67076438 -0.97753187 -0.82776006 ..., -0.4569599 -0.95929131\n -0.19347275]\n [-0.25635923 -0.97753187 0.76651457 ..., 2.18837581 1.35286693\n -0.19347275]\n [-0.48634992 -0.97753187 1.0853695 ..., -0.4569599 0.19678781\n 1.59963548]]\n",
"name": "stdout"
}
]
},
{
"metadata": {},
"cell_type": "markdown",
"source": "### 7. Train - Test Split\n\nSplit the data set into 70% train and hold 30% as a test set."
},
{
"metadata": {
"collapsed": false,
"trusted": true
},
"cell_type": "code",
"source": "#Cross - Validation \nfrom sklearn import cross_validation\nx_train, x_test, y_train, y_test = cross_validation.train_test_split(X, Y, test_size=0.3, random_state=0)",
"execution_count": 19,
"outputs": [
{
"output_type": "stream",
"text": "C:\\Users\\IBM_ADMIN\\Anaconda2\\lib\\site-packages\\sklearn\\cross_validation.py:44: DeprecationWarning: This module was deprecated in version 0.18 in favor of the model_selection module into which all the refactored classes and functions are moved. Also note that the interface of the new CV iterators are different from that of this module. This module will be removed in 0.20.\n \"This module will be removed in 0.20.\", DeprecationWarning)\n",
"name": "stderr"
}
]
},
{
"metadata": {
"collapsed": true
},
"cell_type": "markdown",
"source": "### 8. Train & Select Machine Learning Model\n#### 8.1 Create Linear Regression Model"
},
{
"metadata": {
"collapsed": false,
"trusted": true
},
"cell_type": "code",
"source": "from sklearn.linear_model import LinearRegression\nregmodel = LinearRegression(n_jobs=4)\nregmodel",
"execution_count": 20,
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/plain": "LinearRegression(copy_X=True, fit_intercept=True, n_jobs=4, normalize=False)"
},
"metadata": {},
"execution_count": 20
}
]
},
{
"metadata": {},
"cell_type": "markdown",
"source": "#### 8.2 Make Predictions: Fit Model to Test data"
},
{
"metadata": {
"collapsed": false,
"trusted": true
},
"cell_type": "code",
"source": "regmodel.fit(x_train,y_train)\npredict = regmodel.predict(x_test)",
"execution_count": 21,
"outputs": []
},
{
"metadata": {
"collapsed": false,
"trusted": true
},
"cell_type": "code",
"source": "regmodel.intercept_",
"execution_count": 22,
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/plain": "627.8992948731244"
},
"metadata": {},
"execution_count": 22
}
]
},
{
"metadata": {
"collapsed": false,
"trusted": true
},
"cell_type": "code",
"source": "regmodel.coef_",
"execution_count": 23,
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/plain": "array([ 6.35199647e+02, 5.86543724e-14, 5.44063786e-14,\n 2.30497197e-13, 6.25891533e-14, 2.79931164e-14,\n 7.65826906e-14])"
},
"metadata": {},
"execution_count": 23
}
]
},
{
"metadata": {
"collapsed": true
},
"cell_type": "markdown",
"source": "#### 8.3 Linear Regression Model Acccuracy - RMSE"
},
{
"metadata": {
"collapsed": false,
"trusted": true
},
"cell_type": "code",
"source": "from sklearn.metrics import mean_squared_error\nprice_predict = regmodel.predict(x_train)\nregmodel_mse = mean_squared_error(y_train, price_predict)\nreg_model_rmse = np.sqrt(regmodel_mse)\nreg_model_rmse",
"execution_count": 24,
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/plain": "7.9844345036499249e-13"
},
"metadata": {},
"execution_count": 24
}
]
},
{
"metadata": {},
"cell_type": "markdown",
"source": "### Analysis & Results of the Multiple Linear Regression Model\n\nThis section of the report analyzes a multiple linear regression model between the Y and the independent variables v22,v15,v19,v14,v16,v11,v12,v21.\n\n**Interpretation of the slope** The Interpretation of slope coefficients in this model shows that the value of 6.35199647e+02 for v22 means that price does not increase for each rise of one unit increase in duration. The small value of 4.25570655e-14 for v15 means that price will increase by 4.25570655e-14 units for each rise of one unit in v15. This helps to assess the statistical significance of the estimated causal linkages and determine how little impact these continous variables have on the price.\n\n"
},
{
"metadata": {},
"cell_type": "markdown",
"source": "### Random Forest Regressor Model"
},
{
"metadata": {
"collapsed": false,
"trusted": true
},
"cell_type": "code",
"source": "from sklearn.ensemble import RandomForestRegressor\nranmodel = RandomForestRegressor(n_estimators=30, min_samples_split=28, max_depth=10, max_features='auto')\nranmodel.fit(x_train,y_train)\nprint(\"Predictions:\", ranmodel.predict(x_test))",
"execution_count": 25,
"outputs": [
{
"output_type": "stream",
"text": "('Predictions:', array([ 621.31179357, 980.91050654, 614.04846008, ..., 307.17366619,\n 306.18494624, 170.63928642]))\n",
"name": "stdout"
}
]
},
{
"metadata": {},
"cell_type": "markdown",
"source": "### Random Forest Regressor - Model Accuracy - RMSE"
},
{
"metadata": {
"collapsed": false,
"trusted": true
},
"cell_type": "code",
"source": "ran_price_predict = ranmodel.predict(x_train)\nranmodel_mse = mean_squared_error(y_train, ran_price_predict)\nran_model_rmse = np.sqrt(ranmodel_mse)\nran_model_rmse",
"execution_count": 26,
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/plain": "12.589243609869573"
},
"metadata": {},
"execution_count": 26
}
]
}
],
"metadata": {
"kernelspec": {
"name": "python2",
"display_name": "Python 2",
"language": "python"
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"language_info": {
"mimetype": "text/x-python",
"nbconvert_exporter": "python",
"name": "python",
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"version": "2.7.11",
"file_extension": ".py",
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"gist": {
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"data": {
"description": "Data Science Tutorial - Random Forest Regression.ipynb",
"public": true
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}
},
"nbformat": 4,
"nbformat_minor": 2
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