{ "cells": [ { "cell_type": "markdown", "metadata": { "deletable": false }, "source": [ "# [Introduction to Data Science](http://datascience-intro.github.io/1MS041-2023/) \n", "## 1MS041, 2023 \n", "©2023 Raazesh Sainudiin, Benny Avelin. [Attribution 4.0 International (CC BY 4.0)](https://creativecommons.org/licenses/by/4.0/)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "# CountVectorizer and TFIDFVectorizer" ] }, { "cell_type": "code", "execution_count": 115, "metadata": {}, "outputs": [], "source": [ "from sklearn.feature_extraction.text import CountVectorizer" ] }, { "cell_type": "code", "execution_count": 116, "metadata": {}, "outputs": [], "source": [ "import numpy as np\n", "X_test = np.array(['test of stuff','something of test','stuff of something'])" ] }, { "cell_type": "code", "execution_count": 117, "metadata": {}, "outputs": [], "source": [ "cv = CountVectorizer()" ] }, { "cell_type": "code", "execution_count": 118, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
CountVectorizer()
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On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.
" ], "text/plain": [ "CountVectorizer()" ] }, "execution_count": 118, "metadata": {}, "output_type": "execute_result" } ], "source": [ "cv.fit(X_test)" ] }, { "cell_type": "code", "execution_count": 119, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "array(['of', 'something', 'stuff', 'test'], dtype=object)" ] }, "execution_count": 119, "metadata": {}, "output_type": "execute_result" } ], "source": [ "cv.get_feature_names_out()" ] }, { "cell_type": "code", "execution_count": 120, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "matrix([[1, 0, 1, 1],\n", " [1, 1, 0, 1],\n", " [1, 1, 1, 0]])" ] }, "execution_count": 120, "metadata": {}, "output_type": "execute_result" } ], "source": [ "cv.transform(X_test).todense()" ] }, { "cell_type": "code", "execution_count": 121, "metadata": {}, "outputs": [], "source": [ "from sklearn.feature_extraction.text import TfidfVectorizer" ] }, { "cell_type": "code", "execution_count": 122, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
TfidfVectorizer()
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" ], "text/plain": [ "TfidfVectorizer()" ] }, "execution_count": 122, "metadata": {}, "output_type": "execute_result" } ], "source": [ "tfidf = TfidfVectorizer()\n", "tfidf.fit(X_test)" ] }, { "cell_type": "code", "execution_count": 123, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "array(['of', 'something', 'stuff', 'test'], dtype=object)" ] }, "execution_count": 123, "metadata": {}, "output_type": "execute_result" } ], "source": [ "tfidf.get_feature_names_out()" ] }, { "cell_type": "code", "execution_count": 127, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "matrix([[0.48133417, 0. , 0.61980538, 0.61980538],\n", " [0.48133417, 0.61980538, 0. , 0.61980538],\n", " [0.48133417, 0.61980538, 0.61980538, 0. ]])" ] }, "execution_count": 127, "metadata": {}, "output_type": "execute_result" } ], "source": [ "tfidf_m = tfidf.transform(X_test).todense()\n", "tfidf_m" ] }, { "cell_type": "code", "execution_count": 125, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "1.0" ] }, "execution_count": 125, "metadata": {}, "output_type": "execute_result" } ], "source": [ "np.linalg.norm(tfidf_m[0,:])" ] }, { "cell_type": "code", "execution_count": 128, "metadata": {}, "outputs": [], "source": [ "import pandas as pd\n", "df = pd.read_csv('data/spam.csv',encoding='Latin-1')\n", "X = df['v2']\n", "Y = df['v1']" ] }, { "cell_type": "code", "execution_count": 129, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "0 Go until jurong point, crazy.. Available only ...\n", "1 Ok lar... Joking wif u oni...\n", "2 Free entry in 2 a wkly comp to win FA Cup fina...\n", "3 U dun say so early hor... U c already then say...\n", "4 Nah I don't think he goes to usf, he lives aro...\n", " ... \n", "5567 This is the 2nd time we have tried 2 contact u...\n", "5568 Will Ì_ b going to esplanade fr home?\n", "5569 Pity, * was in mood for that. So...any other s...\n", "5570 The guy did some bitching but I acted like i'd...\n", "5571 Rofl. Its true to its name\n", "Name: v2, Length: 5572, dtype: object" ] }, "execution_count": 129, "metadata": {}, "output_type": "execute_result" } ], "source": [ "X" ] }, { "cell_type": "code", "execution_count": 130, "metadata": {}, "outputs": [], "source": [ "from sklearn.model_selection import train_test_split\n", "X_train,X_test, Y_train, Y_test = train_test_split(X,Y)" ] }, { "cell_type": "code", "execution_count": 131, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
TfidfVectorizer()
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" ], "text/plain": [ "TfidfVectorizer()" ] }, "execution_count": 131, "metadata": {}, "output_type": "execute_result" } ], "source": [ "tfidf.fit(X_train)" ] }, { "cell_type": "code", "execution_count": 132, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
LogisticRegression()
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" ], "text/plain": [ "LogisticRegression()" ] }, "execution_count": 132, "metadata": {}, "output_type": "execute_result" } ], "source": [ "from sklearn.linear_model import LogisticRegression\n", "lr = LogisticRegression()\n", "lr.fit(tfidf.transform(X_train),Y_train)" ] }, { "cell_type": "code", "execution_count": 133, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ " labels precision recall\n", "\n", " spam 0.99 : [0.84,1.00] 0.74 : [0.61,0.87]\n", " ham 0.96 : [0.91,1.00] 1.00 : [0.94,1.00]\n", "\n", " accuracy 0.96 : [0.91,1.00]\n", "\n" ] } ], "source": [ "from Utils import classification_report_interval\n", "print(classification_report_interval(Y_test,lr.predict(tfidf.transform(X_test))))" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "# Feature engineering" ] }, { "cell_type": "code", "execution_count": 134, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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mpgcylindersdisplacementhorsepowerweightaccelerationmodel-year
018.08307.0130.0350412.070
115.08350.0165.0369311.570
218.08318.0150.0343611.070
316.08304.0150.0343312.070
417.08302.0140.0344910.570
\n", "
" ], "text/plain": [ " mpg cylinders displacement horsepower weight acceleration model-year\n", "0 18.0 8 307.0 130.0 3504 12.0 70\n", "1 15.0 8 350.0 165.0 3693 11.5 70\n", "2 18.0 8 318.0 150.0 3436 11.0 70\n", "3 16.0 8 304.0 150.0 3433 12.0 70\n", "4 17.0 8 302.0 140.0 3449 10.5 70" ] }, "execution_count": 134, "metadata": {}, "output_type": "execute_result" } ], "source": [ "import pandas as pd\n", "df = pd.read_csv('data/auto.csv')\n", "df = df.dropna()\n", "df.head(5)" ] }, { "cell_type": "code", "execution_count": 135, "metadata": {}, "outputs": [], "source": [ "X = df['horsepower']\n", "Y = df['mpg']" ] }, { "cell_type": "code", "execution_count": 136, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 136, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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\n", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "import matplotlib.pyplot as plt\n", "plt.scatter(X,Y)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Power, vs miles per gallon.\n", "\n", "Miles per gallon is the inverse of gallon per miles which is fuel consumption." ] }, { "cell_type": "code", "execution_count": 138, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "27.728220057440613" ] }, "execution_count": 138, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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\n", 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "import numpy as np\n", "X = df['horsepower'].to_numpy().reshape(-1,1)\n", "Y = df['mpg'].to_numpy()\n", "\n", "from sklearn.linear_model import LinearRegression\n", "lr = LinearRegression()\n", "\n", "from sklearn.model_selection import train_test_split\n", "X_train,X_test, Y_train, Y_test = train_test_split(X,Y,random_state=0)\n", "lr.fit(X_train,Y_train)\n", "\n", "import matplotlib.pyplot as plt\n", "plt.scatter(lr.predict(X_test),Y_test)\n", "plt.scatter(Y_test,Y_test)\n", "np.mean((lr.predict(X_test)-Y_test)**2)" ] }, { "cell_type": "code", "execution_count": 139, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "24.01416793195116" ] }, "execution_count": 139, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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\n", 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "import numpy as np\n", "X = df['horsepower'].to_numpy().reshape(-1,1)\n", "X = np.concatenate([X,1/X],axis=1) # X = (n_samples,n_features)\n", "Y = df['mpg'].to_numpy()\n", "\n", "from sklearn.linear_model import LinearRegression\n", "lr = LinearRegression()\n", "\n", "from sklearn.model_selection import train_test_split\n", "X_train,X_test, Y_train, Y_test = train_test_split(X,Y,random_state=0)\n", "lr.fit(X_train,Y_train)\n", "\n", "import matplotlib.pyplot as plt\n", "plt.scatter(lr.predict(X_test),Y_test)\n", "plt.scatter(Y_test,Y_test)\n", "np.mean((lr.predict(X_test)-Y_test)**2)" ] }, { "cell_type": "code", "execution_count": 140, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 140, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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\n", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "plt.scatter(X_test[:,0],Y_test)\n", "plt.scatter(X_test[:,0],lr.predict(X_test))" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "# Improving optimization" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "1.123412e6 = 1.123412*10^6\n", "1.234 + 1.123412e6 = 0.000000e6 + 1.123412e6 = 1.123412e6" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "1.23123e-300 = 1.23123*10^(-300)" ] }, { "cell_type": "code", "execution_count": 141, "metadata": {}, "outputs": [], "source": [ "import scipy.io as so\n", "import numpy as np\n", "data = so.loadmat('data/mammography.mat')\n", "\n", "np.random.seed(0)\n", "shuffle_index = np.arange(0,len(data['X']))\n", "np.random.shuffle(shuffle_index)\n", "\n", "X = data['X'][shuffle_index,:]\n", "Y = data['y'][shuffle_index,:].flatten()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Lets make the features very different in scale and see what happens" ] }, { "cell_type": "code", "execution_count": 142, "metadata": {}, "outputs": [], "source": [ "X[:,0] = X[:,0] + 1000" ] }, { "cell_type": "code", "execution_count": 143, "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "/Users/avelin/opt/miniconda3/envs/sage_new/lib/python3.9/site-packages/sklearn/linear_model/_logistic.py:444: ConvergenceWarning: lbfgs failed to converge (status=1):\n", "STOP: TOTAL NO. of ITERATIONS REACHED LIMIT.\n", "\n", "Increase the number of iterations (max_iter) or scale the data as shown in:\n", " https://scikit-learn.org/stable/modules/preprocessing.html\n", "Please also refer to the documentation for alternative solver options:\n", " https://scikit-learn.org/stable/modules/linear_model.html#logistic-regression\n", " n_iter_i = _check_optimize_result(\n" ] }, { "data": { "text/plain": [ "0.983814718769561" ] }, "execution_count": 143, "metadata": {}, "output_type": "execute_result" } ], "source": [ "from sklearn.linear_model import LogisticRegression\n", "lr = LogisticRegression()\n", "lr.fit(X,Y)\n", "lr.score(X,Y)" ] }, { "cell_type": "code", "execution_count": 144, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "0.9837252973262989" ] }, "execution_count": 144, "metadata": {}, "output_type": "execute_result" } ], "source": [ "from sklearn.preprocessing import StandardScaler\n", "sc = StandardScaler()\n", "lr = LogisticRegression()\n", "lr.fit(sc.fit_transform(X),Y)\n", "lr.score(sc.transform(X),Y)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "$$\n", " \\min L(w)\n", "$$" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "$$\n", " \\min L(w) + \\lambda \\|w\\|^2\n", "$$" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "$$\n", " f_w(x) = w_0 + w_1 x \n", "$$" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## How scale and regularization affect eachother\n", "\n", "Lets try to train two models with fairly high regularization and see what happens when we change the scale of the features" ] }, { "cell_type": "code", "execution_count": 145, "metadata": {}, "outputs": [], "source": [ "X = data['X'][shuffle_index,:]\n", "Y = data['y'][shuffle_index,:].flatten()" ] }, { "cell_type": "code", "execution_count": 146, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "0.9837252973262989" ] }, "execution_count": 146, "metadata": {}, "output_type": "execute_result" } ], "source": [ "from sklearn.svm import SVC\n", "from sklearn.linear_model import LogisticRegression\n", "lr = LogisticRegression(C=1/10000)\n", "lr.fit(X*100,Y)\n", "lr.score(X*100,Y)" ] }, { "cell_type": "code", "execution_count": 147, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "0.9767504247518555" ] }, "execution_count": 147, "metadata": {}, "output_type": "execute_result" } ], "source": [ "from sklearn.svm import SVC\n", "from sklearn.linear_model import LogisticRegression\n", "lr = LogisticRegression(C=1/10000)\n", "lr.fit(X,Y)\n", "lr.score(X,Y)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "# Transforming target" ] }, { "cell_type": "code", "execution_count": 148, "metadata": {}, "outputs": [], "source": [ "from sklearn.datasets import fetch_california_housing\n", "X,Y = fetch_california_housing(return_X_y=True)" ] }, { "cell_type": "code", "execution_count": 149, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "0.606232685199805" ] }, "execution_count": 149, "metadata": {}, "output_type": "execute_result" } ], "source": [ "from sklearn.linear_model import LinearRegression\n", "lr = LinearRegression()\n", "lr.fit(X,Y)\n", "lr.score(X,Y)" ] }, { "cell_type": "code", "execution_count": 150, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "(-1.0, 10.0)" ] }, "execution_count": 150, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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\n", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "import matplotlib.pyplot as plt\n", "plt.scatter(lr.predict(X),Y,alpha=0.05)\n", "plt.scatter(lr.predict(X),lr.predict(X))\n", "plt.xlim(-1,10)\n", "plt.ylim(-1,10)" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "log(X)-log(Y) = log(X/Y)" ] }, { "cell_type": "code", "execution_count": 151, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "0.6143678372037653" ] }, "execution_count": 151, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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\n", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "import matplotlib.pyplot as plt\n", "lr = LinearRegression()\n", "lr.fit(X,np.log(Y))\n", "plt.scatter(np.exp(lr.predict(X)),Y,alpha=0.05)\n", "plt.scatter(Y,Y)\n", "plt.xlim(0,7)\n", "plt.ylim(0,7)\n", "lr.score(X,np.log(Y))" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "import matplotlib.pyplot as plt\n", "lr = LinearRegression()\n", "lr.fit(X,np.sqrt(Y))\n", "plt.scatter(np.power(lr.predict(X),2),Y,alpha=0.05)\n", "plt.scatter(Y,Y)\n", "plt.xlim(0,7)\n", "plt.ylim(0,7)\n", "lr.score(X,np.sqrt(Y))\n", "#plt.scatter(np.exp(lr.predict(X)),np.exp(lr.predict(X)))" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "We see that the largest prices seem to be hard to predict, lets see what happens if we remove them" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "_=plt.hist(Y,bins=60)" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "_=plt.hist(np.sqrt(Y[Y < 5]),bins=60)" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "from sklearn.preprocessing import power_transform\n", "_=plt.hist(power_transform(Y[Y < 5].reshape(-1,1)),bins=50)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Playing around with transformations" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "X_new = X[Y < 5,:]\n", "Y_new = Y[Y < 5]" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "from sklearn.preprocessing import PowerTransformer\n", "pw = PowerTransformer()\n", "pw.fit(Y_new.reshape(-1,1))" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "from sklearn.linear_model import LinearRegression\n", "lr = LinearRegression()\n", "lr.fit(X_new,pw.transform(Y_new.reshape(-1,1)).flatten())\n", "\n", "import matplotlib.pyplot as plt\n", "plt.scatter(pw.inverse_transform(lr.predict(X_new).reshape(-1,1)),Y_new,alpha=0.05)\n", "plt.scatter(Y,Y)\n", "plt.xlim(-1,7)\n", "plt.ylim(-1,7)" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "lr.score(X_new,pw.transform(Y_new.reshape(-1,1)).flatten())" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "scrolled": false }, "outputs": [], "source": [ "pw2 = PowerTransformer()\n", "pw2.fit(X_new)\n", "lr = LinearRegression()\n", "lr.fit(pw2.transform(X_new),pw.transform(Y_new.reshape(-1,1)).flatten())\n", "\n", "import matplotlib.pyplot as plt\n", "plt.scatter(pw.inverse_transform(lr.predict(pw2.transform(X_new)).reshape(-1,1)),Y_new,alpha=0.05)\n", "plt.scatter(Y,Y)\n", "plt.xlim(-1,7)\n", "plt.ylim(-1,7)" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "lr.score(pw2.transform(X_new),pw.transform(Y_new.reshape(-1,1)).flatten())" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "# Concentration" ] }, { "cell_type": "code", "execution_count": 152, "metadata": {}, "outputs": [ { "data": { "application/vnd.jupyter.widget-view+json": { "model_id": "669736559f30476891eac84e140248a6", "version_major": 2, "version_minor": 0 }, "text/plain": [ "interactive(children=(IntSlider(value=1, description='n', min=1, step=5), FloatSlider(value=0.5, description='…" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "from ipywidgets import interact, IntSlider, FloatSlider\n", "from Utils import discrete_histogram, bennett_epsilon, epsilon_bounded\n", "import numpy as np\n", "@interact \n", "def concentration(n=IntSlider(1,1,100,5),p=FloatSlider(value=0.5, min=0,max=1,step=0.1)):\n", " import matplotlib.pyplot as plt\n", " X = np.random.binomial(1,p,size=(n,10000))\n", " means = np.mean(X,axis=0)\n", " #print(\"P(mean > mu + 0.3 ) = %.5f <= Chebychev %.5f\" % (np.mean(means > 0.5+0.3),(1/4)/(0.3**2*n)))\n", " #print(\"P(mean > mu + 0.3 ) = %.5f <= Hoeffding %.5f\" % (np.mean(means > 0.5+0.3),np.exp(-2*n*0.3**2)))\n", " print(np.quantile(means,0.025),np.quantile(means,0.975))\n", " epsilon1 = epsilon_bounded(n,1,0.05)\n", " epsilon2 = bennett_epsilon(n,1,np.sqrt((1/2)*p*(1-p)),0.05)\n", " print(\"95%% confidence interval Hoeffding [%.2f, %.2f] for n=%d\" % (np.mean(means)-epsilon1,np.mean(means)+epsilon1,n))\n", " print(\"95%% confidence interval Bennett [%.2f, %.2f] for n=%d\" % (np.mean(means)-epsilon2,np.mean(means)+epsilon2,n))\n", " discrete_histogram(means,normed=True)\n", " plt.xlim(-0.1,1.1)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "# Spam vs not spam, more complete" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "import pandas as pd\n", "df = pd.read_csv('data/spam.csv',encoding='Latin-1')\n", "X = df['v2']\n", "Y = df['v1']\n", "\n", "import pandas as pd\n", "df = pd.read_csv('data/spam.csv',encoding='Latin-1')\n", "\n", "X = df['v2']\n", "Y = df['v1']\n", "\n", "from Utils import train_test_validation\n", "\n", "X_train,X_test, X_valid, Y_train, Y_test, Y_valid = train_test_validation(X,Y)\n", "\n", "from sklearn.pipeline import Pipeline\n", "p = Pipeline([('tfidf',TfidfVectorizer()),('model',LogisticRegression())])\n", "\n", "p.fit(X_train,Y_train)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## If we have no specific cost in mind\n", "\n", "Then simply compute confidence intervals on the standard metrics" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "from Utils import classification_report_interval\n", "print(classification_report_interval(Y_test,p.predict(X_test)))" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Lets define a cost\n", "\n", "If we say something is spam but its not spam, that is quite bad and we could miss important emails. We could say that costs $100$.\n", "\n", "If on the other hand we have spam that is classified as not spam, then that is annoying and we have to manually delete it. Lets say that incurrs a cost of $10$.\n", "\n", "That is, if we define the random variable \n", "$$E_1 = 1_{Y=0, g(X)=1} = 1_{Y=0} 1_{g(X) = 1}$$\n", "and the random variable\n", "$$E_2 = 1_{Y=1, g(X)=0} = 1_{Y=1} 1_{g(X) = 0} = (1-1_{Y=0})(1-1_{g(X)=1}) = 1 - 1_{Y=0} - 1_{g(X)=1} + E_1$$\n", "\n", "Then the cost of a randomly chosen sms is the random variable\n", "$$\n", " C = 100 E_1 + 10 E_2\n", "$$" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "Y_01 = (Y_test == 'spam')*1 # This makes Y_01 into 0 for ham and 1 for spam\n", "g_01 = (p.predict(X_test) == 'spam')*1 # This makes g_01 into 0 for ham and 1 for spam" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "Y_0 = 1-Y_01\n", "g_1 = g_01\n", "E_1 = Y_0*g_1\n", "E_2 = 1-Y_0-g_1+E_1\n", "C = 100*E_1 + 10*E_2" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "We are interested in the expected (average) cost of an sms, we need to estimate $E[C]$.\n", "\n", "We assume that all the sms are i.i.d. so we can use Hoeffdings inequality:\n", "\n", "1. What do we know about $C$? Well the only thing we know is that it is bounded by $0 \\leq C \\leq 100$.\n", "2. Use Hoeffdings inequality to get a confidence interval\n", "3. We will use the `epsilon_bounded` function from `Utils` to do this" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "from Utils import epsilon_bounded, print_confidence_interval\n", "eps = epsilon_bounded(len(C),100,0.05)\n", "mean = np.mean(C)\n", "print_confidence_interval(mean,eps,min_value=0,max_value=100)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "However, we know that we can adjust the threshold of our model, and perhaps the cost will be different for another threshold?" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "def cost(threshold):\n", " Y_01 = (Y_test == 'spam')*1 # This makes Y_01 into 0 for ham and 1 for spam\n", " g_01 = (p.predict_proba(X_test)[:,1] >= threshold)*1 # This makes g_01 into 0 for ham and 1 for spam\n", " Y_0 = 1-Y_01\n", " g_1 = g_01\n", " E_1 = Y_0*g_1\n", " E_2 = 1-Y_0-g_1+E_1\n", " C = 100*E_1 + 10*E_2\n", " \n", " return np.mean(C)" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "thresholds = np.linspace(0,1,100)\n", "costs = [cost(t) for t in thresholds]" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "import matplotlib.pyplot as plt\n", "plt.plot(thresholds, np.log(costs))" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Now we can compute the confidence interval in the same way, but on the validation data" ] } ], "metadata": { "kernelspec": { "display_name": "Python 3 (ipykernel)", "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": "3.9.13" }, "lx_course_instance": "2023", "lx_course_name": "Introduction to Data Science", "lx_course_number": "1MS041" }, "nbformat": 4, "nbformat_minor": 5 }