diff --git a/Paranormal_or_skeptic.ipynb b/Paranormal_or_skeptic.ipynb index ebc2e7e..458727c 100644 --- a/Paranormal_or_skeptic.ipynb +++ b/Paranormal_or_skeptic.ipynb @@ -14,6 +14,37 @@ } }, "cells": [ + { + "cell_type": "code", + "metadata": { + "id": "dZUIeB9Q8rv3", + "colab_type": "code", + "colab": { + "base_uri": "https://localhost:8080/", + "height": 136 + }, + "outputId": "95512ec2-2ea3-4ff5-bc08-09ee3b99c39c" + }, + "source": [ + "!git clone git://gonito.net/paranormal-or-skeptic " + ], + "execution_count": 5, + "outputs": [ + { + "output_type": "stream", + "text": [ + "Cloning into 'paranormal-or-skeptic'...\n", + "remote: Enumerating objects: 3583, done.\u001b[K\n", + "remote: Counting objects: 100% (3583/3583), done.\u001b[K\n", + "remote: Compressing objects: 100% (3188/3188), done.\u001b[K\n", + "remote: Total 3583 (delta 789), reused 2704 (delta 338)\n", + "Receiving objects: 100% (3583/3583), 202.38 MiB | 4.18 MiB/s, done.\n", + "Resolving deltas: 100% (789/789), done.\n" + ], + "name": "stdout" + } + ] + }, { "cell_type": "markdown", "metadata": { @@ -30,7 +61,7 @@ "metadata": { "id": "NQFKg_czGeRA", "colab_type": "code", - "outputId": "60d1c52a-8b42-4a26-d878-67f284589917", + "outputId": "4cf38154-be9f-48b4-e0ea-cfac084e795a", "colab": { "base_uri": "https://localhost:8080/", "height": 34 @@ -39,7 +70,7 @@ "source": [ "!xzcat train/in.tsv.xz | wc -l" ], - "execution_count": 0, + "execution_count": 11, "outputs": [ { "output_type": "stream", @@ -79,8 +110,10 @@ "source": [ "from sklearn.feature_extraction.text import CountVectorizer, TfidfTransformer\n", "from sklearn.pipeline import Pipeline\n", - "from sklearn.linear_model import SGDClassifier\n", - "from sklearn.naive_bayes import MultinomialNB,ComplementNB,BernoulliNB,GaussianNB" + "from sklearn.linear_model import SGDClassifier, LogisticRegression\n", + "from sklearn.svm import LinearSVC\n", + "from sklearn.naive_bayes import MultinomialNB,ComplementNB,BernoulliNB,GaussianNB\n", + "from sklearn.neural_network import MLPClassifier" ], "execution_count": 0, "outputs": [] @@ -174,7 +207,7 @@ "metadata": { "id": "dcjUSa7f7Wex", "colab_type": "code", - "outputId": "9fa0ca70-0516-4656-a1d5-641e5b0f41ff", + "outputId": "f9ade29f-f746-4dd2-eb79-25845095a9f6", "colab": { "base_uri": "https://localhost:8080/", "height": 204 @@ -183,7 +216,7 @@ "source": [ "train_set.sample(5)" ], - "execution_count": 0, + "execution_count": 18, "outputs": [ { "output_type": "execute_result", @@ -216,43 +249,43 @@ " \n", " \n", " \n", - " 103770\n", - " Holy crap. I don't think I've seen or heard o...\n", - " 2010-07-16 19:27:08\n", - " 16\n", - " 7\n", - " 2010\n", + " 112652\n", + " As i hovered over that link I was expecting r/...\n", + " 2012-03-23 13:34:29\n", + " 23\n", + " 3\n", + " 2012\n", " \n", " \n", - " 240391\n", - " You lost all pretense of civility with your ar...\n", - " 2010-09-30 12:18:36\n", - " 30\n", - " 9\n", - " 2010\n", + " 172265\n", + " Caesarean section is now the new natural child...\n", + " 2012-04-19 14:28:59\n", + " 19\n", + " 4\n", + " 2012\n", " \n", " \n", - " 220910\n", - " What do people think of ghost adventures? Cur...\n", - " 2012-08-21 19:59:56\n", - " 21\n", + " 150100\n", + " The Somerton Man reminds me of the [Lead Masks...\n", + " 2012-08-04 21:21:56\n", + " 4\n", " 8\n", " 2012\n", " \n", " \n", - " 39644\n", - " Congrats on getting the joke.\n", - " 2011-07-29 18:19:46\n", - " 29\n", - " 7\n", - " 2011\n", + " 153335\n", + " As a skeptic, I demand this man provide eviden...\n", + " 2012-06-20 04:44:02\n", + " 20\n", + " 6\n", + " 2012\n", " \n", " \n", - " 220867\n", - " We live in a world where any media can be copi...\n", - " 2012-07-18 08:53:24\n", - " 18\n", - " 7\n", + " 149621\n", + " It's a fucking bug.\n", + " 2012-11-15 02:29:24\n", + " 15\n", + " 11\n", " 2012\n", " \n", " \n", @@ -261,11 +294,11 @@ ], "text/plain": [ " text ... year\n", - "103770 Holy crap. I don't think I've seen or heard o... ... 2010\n", - "240391 You lost all pretense of civility with your ar... ... 2010\n", - "220910 What do people think of ghost adventures? Cur... ... 2012\n", - "39644 Congrats on getting the joke. ... 2011\n", - "220867 We live in a world where any media can be copi... ... 2012\n", + "112652 As i hovered over that link I was expecting r/... ... 2012\n", + "172265 Caesarean section is now the new natural child... ... 2012\n", + "150100 The Somerton Man reminds me of the [Lead Masks... ... 2012\n", + "153335 As a skeptic, I demand this man provide eviden... ... 2012\n", + "149621 It's a fucking bug. ... 2012\n", "\n", "[5 rows x 5 columns]" ] @@ -273,7 +306,7 @@ "metadata": { "tags": [] }, - "execution_count": 12 + "execution_count": 18 } ] }, @@ -320,29 +353,33 @@ "metadata": { "id": "CeYlhwda9Sa7", "colab_type": "code", - "outputId": "607d4f8f-f632-4d41-a1ab-e5d020cc00ae", + "outputId": "61a66f28-85b6-452d-bdd0-180772498e34", "colab": { "base_uri": "https://localhost:8080/", - "height": 34 + "height": 102 } }, "source": [ - "bayes = MultinomialNB(alpha=0.4)\n", + "bayes = LogisticRegression(max_iter=1000)\n", "bayes.fit(X,y)" ], - "execution_count": 0, + "execution_count": 176, "outputs": [ { "output_type": "execute_result", "data": { "text/plain": [ - "MultinomialNB(alpha=0.4, class_prior=None, fit_prior=True)" + "LogisticRegression(C=1.0, class_weight=None, dual=False, fit_intercept=True,\n", + " intercept_scaling=1, l1_ratio=None, max_iter=1000,\n", + " multi_class='auto', n_jobs=None, penalty='l2',\n", + " random_state=None, solver='lbfgs', tol=0.0001, verbose=0,\n", + " warm_start=False)" ] }, "metadata": { "tags": [] }, - "execution_count": 15 + "execution_count": 176 } ] }, @@ -367,7 +404,9 @@ "def predict_data(data):\n", " prepared = prepare_data(data)\n", " vectorized = vectorize.transform(data[\"text\"])\n", - " predicted = bayes.predict(vectorized)\n", + " predicted = bayes.predict_proba(vectorized)[:,1]\n", + " predicted[predicted < 0.05] = 0.05\n", + " predicted[predicted > 0.95] = 0.95\n", " return predicted" ], "execution_count": 0, @@ -391,28 +430,29 @@ "metadata": { "id": "yigVrrVJHkob", "colab_type": "code", - "outputId": "9491f926-94a3-4310-9f63-be937663489d", + "outputId": "42a53652-60ed-4a11-85cf-683ba4b91d23", "colab": { "base_uri": "https://localhost:8080/", - "height": 34 + "height": 51 } }, "source": [ - "np.mean(dev_predicted == expected_dev[\"class\"])" + "dev_predicted" ], - "execution_count": 0, + "execution_count": 195, "outputs": [ { "output_type": "execute_result", "data": { "text/plain": [ - "0.8201820940819423" + "array([0.05 , 0.75847969, 0.86484399, ..., 0.0650311 , 0.95 ,\n", + " 0.37791457])" ] }, "metadata": { "tags": [] }, - "execution_count": 19 + "execution_count": 195 } ] }, @@ -471,8 +511,8 @@ "colab": {} }, "source": [ - "np.savetxt('test-A/out.tsv', test_predicted, '%c')\n", - "np.savetxt('dev-0/out.tsv', dev_predicted, '%c')" + "np.savetxt('test-A/out.tsv', test_predicted, '%f')\n", + "np.savetxt('dev-0/out.tsv', dev_predicted, '%f')" ], "execution_count": 0, "outputs": [] @@ -506,21 +546,25 @@ "metadata": { "id": "oEkjIcwe8zef", "colab_type": "code", - "outputId": "cdb6473e-4eb9-48a7-cc25-25a193cc9194", + "outputId": "16433b8f-9e3a-4e49-db5d-dc7373c3c675", "colab": { "base_uri": "https://localhost:8080/", - "height": 34 + "height": 102 } }, "source": [ "!./geval -t \"dev-0\"" ], - "execution_count": 0, + "execution_count": 214, "outputs": [ { "output_type": "stream", "text": [ - "0.8202\n" + "Likelihood\t0.6707\n", + "Accuracy\t0.8151\n", + "F1.0\t0.7197\n", + "Precision\t0.7762\n", + "Recall\t0.6710\n" ], "name": "stdout" } diff --git a/dev-0/out.tsv b/dev-0/out.tsv index e572e45..4bdb0a0 100644 --- a/dev-0/out.tsv +++ b/dev-0/out.tsv @@ -1,5272 +1,5272 @@ -0 -1 -1 -0 -0 -0 -0 -0 -0 -1 -0 -0 -0 -1 -0 -1 -0 -1 -0 -1 -0 -0 -1 -1 -1 -0 -1 -1 -0 -1 -0 -1 -0 -0 -0 -0 -0 -0 -1 -0 -0 -0 -0 -1 -0 -0 -1 -0 -0 -1 -1 -0 -1 -0 -1 -0 -0 -0 -0 -0 -1 -1 -0 -1 -0 -1 -0 -1 -1 -1 -0 -0 -0 -1 -0 -1 -0 -0 -0 -0 -1 -0 -0 -0 -0 -0 -1 -1 -0 -1 -0 -0 -0 -0 -0 -0 -1 -0 -1 -0 -0 -1 -1 -1 -0 -1 -0 -1 -0 -0 -0 -0 -0 -0 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+0.279949 +0.050000 +0.071635 +0.050000 +0.252026 +0.050000 +0.950000 +0.050000 +0.050000 +0.950000 +0.050000 +0.371327 +0.050000 +0.857967 +0.121273 +0.496941 +0.109647 +0.899713 +0.065031 +0.950000 +0.377915 diff --git a/paranormal_or_skeptic.py b/paranormal_or_skeptic.py index a89e119..9ae299d 100644 --- a/paranormal_or_skeptic.py +++ b/paranormal_or_skeptic.py @@ -5,10 +5,12 @@ Automatically generated by Colaboratory. Original file is located at https://colab.research.google.com/drive/1JI_RWapDbABFZPc4NDhU-zQlZiIiXk58 - -# Loading Data """ +!git clone git://gonito.net/paranormal-or-skeptic + +"""# Loading Data""" + !xzcat train/in.tsv.xz | wc -l import matplotlib.pyplot as plt @@ -21,8 +23,10 @@ import datetime from sklearn.feature_extraction.text import CountVectorizer, TfidfTransformer from sklearn.pipeline import Pipeline -from sklearn.linear_model import SGDClassifier +from sklearn.linear_model import SGDClassifier, LogisticRegression +from sklearn.svm import LinearSVC from sklearn.naive_bayes import MultinomialNB,ComplementNB,BernoulliNB,GaussianNB +from sklearn.neural_network import MLPClassifier def load_set(path, isTest): dataset = pd.read_csv(path+"/in.tsv.xz", delimiter="\t",header=None,names=["text","date"],quoting=csv.QUOTE_NONE) @@ -58,7 +62,7 @@ vectorized = vectorize.fit_transform(train_set["text"]) X = vectorized y = expected_train["class"] -bayes = MultinomialNB(alpha=0.4) +bayes = LogisticRegression(max_iter=1000) bayes.fit(X,y) """# Predict and evaluate""" @@ -66,12 +70,14 @@ bayes.fit(X,y) def predict_data(data): prepared = prepare_data(data) vectorized = vectorize.transform(data["text"]) - predicted = bayes.predict(vectorized) + predicted = bayes.predict_proba(vectorized)[:,1] + predicted[predicted < 0.05] = 0.05 + predicted[predicted > 0.95] = 0.95 return predicted dev_predicted = predict_data(dev_set) -np.mean(dev_predicted == expected_dev["class"]) +dev_predicted test_predicted = predict_data(test_set) @@ -82,8 +88,8 @@ dev_predicted = np.array([item.strip() for item in dev_predicted]) """**Save to file**""" -np.savetxt('test-A/out.tsv', test_predicted, '%c') -np.savetxt('dev-0/out.tsv', dev_predicted, '%c') +np.savetxt('test-A/out.tsv', test_predicted, '%f') +np.savetxt('dev-0/out.tsv', dev_predicted, '%f') """**Check geval output**""" diff --git a/test-A/out.tsv b/test-A/out.tsv index d5c993b..2bb12df 100644 --- a/test-A/out.tsv +++ b/test-A/out.tsv @@ 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