Skip to content

Instantly share code, notes, and snippets.

@gpopovic
Created August 10, 2016 05:57
Show Gist options
  • Save gpopovic/3f3024fe26b516b672a82f773685fec4 to your computer and use it in GitHub Desktop.
Save gpopovic/3f3024fe26b516b672a82f773685fec4 to your computer and use it in GitHub Desktop.
Goran
{
"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# SVD and Latent Semantic Analysis (LSA)\n",
"\n",
"Singular Value Decomposition (SVD) applied to text documents is often referred to as _Latent Semantic Analysis_ (LSA).\n",
"\n",
"Let's $A$ be our $N \\times n$ feature matrix with $N$ samples and $n$ features, and let's write the SVD as follows, trunacted to some dimension $k < n$:\n",
"\n",
"\\begin{align}\n",
"A = U \\Sigma V^{T}\n",
"\\end{align}\n",
"\n",
"Each of these matrices represents some grouping the data:\n",
"- $U$ ($N \\times k$) represents how each datapoint relates to some latent concept,\n",
"- $V$ ($n \\times k$) represents how each concept relates to each original feature, and\n",
"- $\\Sigma$ ($k \\times k$) represents the strength of each of those concepts in the dataset.\n",
"\n",
"This reduces the number of dimensions from $n$ to $k$, since instead of modelling our data for each feature, we now model our data for each concept. Our intuition is that datapoints with similar relevant features will get similar concepts.\n",
"\n",
"A very concrete example of this is text classification, in which case this method is often called _Latent Semantic Analysis_ (LSA). As always with Natural Language Processing (NLP), we transform our $N$ documents into a $N \\times n$ feature matrix, where each column represents a certain word or n-gram (e.g., using `CountVectorizer`). \n",
"\n",
"This notebook demonstrates SVD and LSA with a simple example."
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"#### Import code and data"
]
},
{
"cell_type": "code",
"execution_count": 1,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"import numpy as np\n",
"import pandas as pd\n",
"from sklearn.datasets import fetch_20newsgroups\n",
"from sklearn.decomposition import TruncatedSVD\n",
"from sklearn.feature_extraction.text import TfidfVectorizer, CountVectorizer\n",
"from sklearn.pipeline import make_pipeline\n",
"from sklearn.preprocessing import Normalizer\n",
"import seaborn\n",
"from matplotlib import pyplot as plt\n",
"%matplotlib inline"
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {
"collapsed": false
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Loading 20-newsgroups dataset for categories: ['talk.religion.misc', 'comp.graphics', 'sci.space']\n",
"2588 article in 3 categories\n",
"Wall time: 787 ms\n"
]
}
],
"source": [
"%%time\n",
"categories = ['talk.religion.misc', 'comp.graphics', 'sci.space',]\n",
"print \"Loading 20-newsgroups dataset for categories:\", categories\n",
"dataset = fetch_20newsgroups(subset='all', categories=categories, shuffle=True)\n",
"print \"%d article in %d categories\" % (len(dataset.data), len(dataset.target_names))\n",
"labels = dataset.target\n",
"true_k = np.unique(labels).shape[0]"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"#### Feature extraction\n",
"Extract features from the training dataset using a sparse vectorizer."
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {
"collapsed": false
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Dimensions feature matrix: (2588, 10000)\n",
"Wall time: 1.36 s\n"
]
}
],
"source": [
"%%time\n",
"vectorizer = CountVectorizer(stop_words='english', max_features=10000, min_df=2, max_df=0.5)\n",
"X = vectorizer.fit_transform(dataset.data)\n",
"n_samples, n_features = X.shape\n",
"print \"Dimensions feature matrix:\", X.shape"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"#### Dimension reduction\n",
"We could reduce the number of dimensions by performing a SVD. We hope that we could describe most of the data in a much lower-dimensional space, in which the dimensions represent topics (or concepts, or _latent semantics_) rather than just words."
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"n_components = 150"
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {
"collapsed": false
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Explained variance of the SVD step: 82%\n",
"Dimensions feature matrix (old): (2588, 10000)\n",
"Dimensions feature matrix (new): (2588L, 150L)\n",
"Wall time: 998 ms\n"
]
}
],
"source": [
"%%time\n",
"svd = TruncatedSVD(n_components)\n",
"lsa = make_pipeline(svd, Normalizer(copy=False))\n",
"X_red = lsa.fit_transform(X)\n",
"explained_variance = svd.explained_variance_ratio_.sum()\n",
"print \"Explained variance of the SVD step: %d%%\" % (explained_variance * 100)\n",
"print \"Dimensions feature matrix (old):\", X.shape\n",
"print \"Dimensions feature matrix (new):\", X_red.shape"
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"image/png": "iVBORw0KGgoAAAANSUhEUgAAAXoAAAEKCAYAAAAcgp5RAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\ngl5EJMv9f8LBTm5Xcr72AAAAAElFTkSuQmCC\n",
"text/plain": [
"<matplotlib.figure.Figure at 0xa533748>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"f = plt.plot(svd.explained_variance_ratio_.cumsum()) # these are the singular values \n",
"f = plt.title(\"Explained variance by number of components\")"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Great, we can describe almost 80% of our variance by just 150 dimensions, and even better, 50% of our varaince by only a handful of components.\n",
"\n",
"Each component is made out of a certain word combination with different weights. Let's have a look at themost important components."
]
},
{
"cell_type": "code",
"execution_count": 7,
"metadata": {
"collapsed": false
},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"__main__.py:8: FutureWarning: sort is deprecated, use sort_values(inplace=True) for INPLACE sorting\n"
]
},
{
"data": {
"image/png": "iVBORw0KGgoAAAANSUhEUgAABZkAAAHvCAYAAAA2B9GQAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nAAAAAElFTkSuQmCC\n",
"text/plain": [
"<matplotlib.figure.Figure at 0xd8c5240>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"words = np.array(vectorizer.get_feature_names())\n",
"top_words = 10\n",
"n_rows, n_cols = 2, 4\n",
"top_components = n_rows * n_cols\n",
"f, axes = plt.subplots(n_rows, n_cols, figsize=(20, 7))\n",
"for no, component in enumerate(svd.components_[:top_components]):\n",
" ax = axes[no / n_cols][no % n_cols]\n",
" s = pd.Series(svd.components_[no], index=words).sort(inplace=False)[-top_words:]\n",
" s.plot(kind='barh', ax=ax, title=\"Component %d\\nexplained variance %4.1f\" % \n",
" (no, 100 * svd.explained_variance_ratio_[no]))\n",
"f = plt.tight_layout()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Very clear results! \n",
"\n",
"Let's look at our documents and see how an article is represented in these dimensions."
]
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 2",
"language": "python",
"name": "python2"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 2
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython2",
"version": "2.7.12"
}
},
"nbformat": 4,
"nbformat_minor": 0
}
Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment