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Created January 4, 2018 07:39
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NTU Machine Learning 2017 Fall - Assignment 1
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{
"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Assignment 1 - Predicting PM2.5\n",
"\n",
"https://ntumlta.github.io/2017fall-ml-hw1/"
]
},
{
"cell_type": "code",
"execution_count": 1,
"metadata": {},
"outputs": [],
"source": [
"%matplotlib inline\n",
"import matplotlib.pyplot as plt\n",
"import numpy as np\n",
"import pandas as pd"
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {},
"outputs": [],
"source": [
"def slide_window_indexer(data_size, window_size=9, stride=1):\n",
" win = np.arange(window_size)[np.newaxis, :]\n",
" strides = np.arange((data_size - window_size) // stride + 1, step=stride)[:, np.newaxis]\n",
" return win + strides\n",
"\n",
"def gen_train_data(df):\n",
" data = df.loc[:, '0':'23'].values\n",
" data = data.reshape(12, 20, 18, 24).swapaxes(2, 3)\n",
" data = data.reshape(12, -1, 18)\n",
" y = data[:, 9:, 9].ravel()\n",
" x = data[:, slide_window_indexer(data.shape[1] - 1, window_size=9, stride=1)]\n",
" x = x.reshape(-1, 9 * 18)\n",
" return x, y\n",
"\n",
"def gen_test_data(df):\n",
" data = df.loc[:, 2:10].values\n",
" x = data.reshape(-1, 18, 9).swapaxes(1, 2)\n",
" x = x.reshape(-1, 9 * 18)\n",
" return x\n",
"\n",
"def std_scale(data):\n",
" return (data - data.mean(axis=0)) / data.std(axis=0)\n",
"\n",
"def rmse(y_true, y_pred):\n",
" return np.sqrt(np.mean((y_true - y_pred) ** 2))\n",
"\n",
"class AverageBaseline:\n",
" \"\"\"\n",
" predict pm2.5 using the average\n",
" \"\"\"\n",
" def __init__(self):\n",
" pass\n",
" \n",
" def fit(self, X, y):\n",
" self._average_y = y.mean()\n",
" \n",
" def predict(self, X):\n",
" return np.full(len(X), self._average_y)\n",
" \n",
"class LastHourBaseline:\n",
" \"\"\"\n",
" predict pm2.5 using last hour's value\n",
" \"\"\"\n",
" def __init__(self):\n",
" pass\n",
" \n",
" def predict(self, X):\n",
" return X.reshape(-1, 9, 18)[:, -1, 9]\n",
"\n",
"class CloseFormLinearRegression:\n",
" \"\"\"\n",
" linear regression using closed-form solution\n",
" \"\"\"\n",
" def __init__(self, intercept=True):\n",
" self._intercept = intercept\n",
" \n",
" def fit(self, X, y):\n",
" if self._intercept:\n",
" X = np.c_[X, np.ones(len(X))]\n",
" pseudo_inv = np.linalg.inv(np.matmul(X.T, X))\n",
" self._w = np.matmul(np.matmul(pseudo_inv, X.T), y)\n",
" \n",
" def predict(self, X):\n",
" if self._intercept:\n",
" X = np.c_[X, np.ones(len(X))]\n",
" return np.dot(X, self._w)\n",
" \n",
"class AdaLinearRegression:\n",
" \"\"\"\n",
" linear regression using gradient descent\n",
" \"\"\"\n",
" def __init__(self, lr=10, n_steps=20000, intercept=True, l1=0, l2=0):\n",
" self._lr = lr\n",
" self._l1 = l1\n",
" self._l2 = l2\n",
" self._n_steps = n_steps\n",
" self._intercept = intercept\n",
" \n",
" def fit(self, X, y, verbose=True):\n",
" assert len(X) == len(y)\n",
" if self._intercept:\n",
" w = np.zeros(X.shape[1] + 1)\n",
" X = np.c_[X, np.ones(len(X))]\n",
" else:\n",
" w = np.zeros(X.shape[1])\n",
" s_grad = np.zeros_like(w)\n",
" for i in range(1, self._n_steps + 1):\n",
" hypo = np.dot(X, w)\n",
" loss = hypo - y\n",
" cost = np.sum(loss ** 2) / len(y)\n",
" cost_a = np.sqrt(cost)\n",
" grad = np.dot(X.T, loss) + self._l1 * np.sign(w) + self._l2 * w\n",
" s_grad += grad ** 2\n",
" ada = np.sqrt(s_grad)\n",
" w = w - self._lr * grad / ada\n",
" if verbose and i % 2000 == 0:\n",
" print('iter %5d | cost: %.5f' % (i, cost_a))\n",
" self._w = w\n",
" \n",
" def predict(self, X):\n",
" if self._intercept:\n",
" X = np.c_[X, np.ones(len(X))]\n",
" return np.dot(X, self._w)"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {},
"outputs": [],
"source": [
"TRAIN_FILE = './train.csv'\n",
"TEST_FILE = './test.csv'\n",
"TEST_ANS = './ans.csv'\n",
"\n",
"train_df = pd.read_csv(TRAIN_FILE, encoding='big5', na_values='NR')\n",
"test_df = pd.read_csv(TEST_FILE, encoding='big5', header=None, na_values='NR')\n",
"test_ans = pd.read_csv(TEST_ANS)\n",
"\n",
"train_df = train_df.fillna(0)\n",
"test_df = test_df.fillna(0)\n",
"\n",
"train_x, train_y = gen_train_data(train_df)\n",
"test_x = gen_test_data(test_df)\n",
"test_y = test_ans['value'].values"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Last hour baseline\n",
"\n",
"predict using the last hour's pm2.5"
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"rmse (train): 6.87400510719\n",
"rmse (test): 7.31949451807\n"
]
}
],
"source": [
"last_hour_baseline = LastHourBaseline()\n",
"print('rmse (train):', rmse(train_y, last_hour_baseline.predict(train_x)))\n",
"print('rmse (test):', rmse(test_y, last_hour_baseline.predict(test_x)))"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Average baseline\n",
"\n",
"predict using average pm2.5 value"
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"rmse (train): 16.6132972856\n",
"rmse (test): 23.1919505657\n"
]
}
],
"source": [
"avg_baseline = AverageBaseline()\n",
"avg_baseline.fit(train_x, train_y)\n",
"print('rmse (train):', rmse(train_y, avg_baseline.predict(train_x)))\n",
"print('rmse (test):', rmse(test_y, avg_baseline.predict(test_x)))"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Linear regression using close form solution"
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"rmse (train): 5.67951832918\n",
"rmse (test): 6.57001391551\n"
]
}
],
"source": [
"close_form_lr = CloseFormLinearRegression()\n",
"close_form_lr.fit(train_x, train_y)\n",
"print('rmse (train):', rmse(train_y, close_form_lr.predict(train_x)))\n",
"print('rmse (test):', rmse(test_y, close_form_lr.predict(test_x)))"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Linear regression using adagrad"
]
},
{
"cell_type": "code",
"execution_count": 7,
"metadata": {},
"outputs": [],
"source": [
"weights = []\n",
"cs = [-1, 0, 1, 2, 3, 4, 5]\n",
"for c in cs:\n",
" ada_lr = AdaLinearRegression(n_steps=20000, l1=10 ** c)\n",
" ada_lr.fit(train_x, train_y, verbose=False)\n",
" weights.append(ada_lr._w)"
]
},
{
"cell_type": "code",
"execution_count": 8,
"metadata": {},
"outputs": [
{
"data": {
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\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x7f1e53299ac8>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"plt.figure(figsize=(16, 10))\n",
"for w in np.array(weights).T:\n",
" plt.plot(cs, w)"
]
},
{
"cell_type": "code",
"execution_count": 9,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"rmse (train): 5.7620705543\n",
"rmse (test): 6.57248241612\n"
]
}
],
"source": [
"ada_lr = AdaLinearRegression(n_steps=20000, l1=0.1)\n",
"ada_lr.fit(train_x, train_y, verbose=False)\n",
"print('rmse (train):', rmse(train_y, ada_lr.predict(train_x)))\n",
"print('rmse (test):', rmse(test_y, ada_lr.predict(test_x)))"
]
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.5.2"
}
},
"nbformat": 4,
"nbformat_minor": 2
}
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