Jonas: some stuff
This commit is contained in:
Jonas Weinz
parent
42ac5d8d81
commit
9769375e17
@ -14,17 +14,21 @@
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"* Tutorial on Datacamp: https://www.datacamp.com/community/tutorials/scikit-learn-fake-news\n",
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"\n",
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"* liar dataset paper: https://www.cs.ucsb.edu/~william/papers/acl2017.pdf\n",
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" * dataset: https://www.cs.ucsb.edu/~william/data/liar_dataset.zip\n",
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"\n",
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" * dataset: https://www.cs.ucsb.edu/~william/data/liar_dataset.zip"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## Dependencies for this Notebook:\n",
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"* library [rdflib](https://github.com/RDFLib/rdflib)\n",
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" * install: `pip3 install rdflib`\n",
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"* "
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" * install: `pip3 install rdflib`\n"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 4,
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"execution_count": 1,
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"metadata": {},
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"outputs": [
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{
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@ -41,7 +45,7 @@
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},
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{
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"cell_type": "code",
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"execution_count": 31,
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"execution_count": 21,
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"metadata": {},
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"outputs": [],
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"source": [
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@ -49,9 +53,65 @@
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"import numpy as np\n",
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"import itertools\n",
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"import sklearn.utils as sku\n",
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"from sklearn.feature_extraction.text import CountVectorizer, TfidfVectorizer, HashingVectorizer\n",
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"from sklearn.model_selection import train_test_split\n",
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"from sklearn.linear_model import PassiveAggressiveClassifier\n",
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"from sklearn.naive_bayes import MultinomialNB\n",
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"from sklearn import metrics\n",
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"import matplotlib.pyplot as plt\n",
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"from pprint import pprint as pp\n",
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"import os"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## Tools used later"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 37,
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"metadata": {},
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"outputs": [],
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"source": [
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"def plot_confusion_matrix(cm, classes,\n",
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" title,\n",
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" normalize=False,\n",
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" cmap=plt.cm.Blues):\n",
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" fig_1, ax_1 = plt.subplots()\n",
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" \"\"\"\n",
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" See full source and example: \n",
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" http://scikit-learn.org/stable/auto_examples/model_selection/plot_confusion_matrix.html\n",
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" \n",
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" This function prints and plots the confusion matrix.\n",
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" Normalization can be applied by setting `normalize=True`.\n",
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" \"\"\"\n",
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" plt.imshow(cm, interpolation='nearest', cmap=cmap)\n",
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" plt.title('Confusion Matrix for: ' + title)\n",
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" plt.colorbar()\n",
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" tick_marks = np.arange(len(classes))\n",
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" plt.xticks(tick_marks, classes, rotation=45)\n",
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" plt.yticks(tick_marks, classes)\n",
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"\n",
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" if normalize:\n",
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" cm = cm.astype('float') / cm.sum(axis=1)[:, np.newaxis]\n",
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" print(\"Normalized confusion matrix\")\n",
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" else:\n",
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" print('Confusion matrix, without normalization')\n",
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"\n",
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" thresh = cm.max() / 2.\n",
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" for i, j in itertools.product(range(cm.shape[0]), range(cm.shape[1])):\n",
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" plt.text(j, i, cm[i, j],\n",
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" horizontalalignment=\"center\",\n",
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" color=\"white\" if cm[i, j] > thresh else \"black\")\n",
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"\n",
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" plt.tight_layout()\n",
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" plt.ylabel('True label')\n",
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" plt.xlabel('Predicted label')"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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@ -63,7 +123,7 @@
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},
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{
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"cell_type": "code",
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"execution_count": 18,
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"execution_count": 3,
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"metadata": {},
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"outputs": [
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{
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@ -103,37 +163,16 @@
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" UNZIPOPT: [none]\n",
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" ZIPINFO: [none]\n",
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" ZIPINFOOPT: [none]\n",
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"Archive: liar_dataset.zip\n",
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" inflating: README \n",
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" inflating: test.tsv \n",
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" inflating: train.tsv \n",
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" inflating: valid.tsv \n",
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"================================================================================\n",
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"successfully finished action: downloading and unpacking https://www.cs.ucsb.edu/~william/data/liar_dataset.zip if not already existing\n",
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"================================================================================\n",
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"================================================================================\n",
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"downloading and unpacking https://raw.githubusercontent.com/GeorgeMcIntire/fake_real_news_dataset/master/fake_or_real_news.csv.zip if not already existing\n",
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"================================================================================\n",
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"Archive: fake_or_real_news.csv.zip\n",
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" inflating: fake_or_real_news.csv \n",
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" creating: __MACOSX/\n",
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" inflating: __MACOSX/._fake_or_real_news.csv \n",
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"================================================================================\n",
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"successfully finished action: downloading and unpacking https://raw.githubusercontent.com/GeorgeMcIntire/fake_real_news_dataset/master/fake_or_real_news.csv.zip if not already existing\n",
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"================================================================================\n"
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]
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},
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{
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"name": "stderr",
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"output_type": "stream",
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"100 989k 100 989k 0 0 366k 0 0:00:02 0:00:02 --:--:-- 366k\n",
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"source": [
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"cell_type": "code",
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"execution_count": 36,
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"cell_type": "code",
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"execution_count": 37,
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"outputs": [
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@ -321,28 +360,274 @@
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{
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"cell_type": "code",
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"execution_count": null,
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"execution_count": 6,
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"metadata": {},
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"outputs": [],
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"source": [
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"def create_test_dset(dset, cutoff=0.7):\n",
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" shuffled = sku.shuffle(dset)\n",
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"def create_training_and_test_set(dset, cutoff=0.7):\n",
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" shuffled = sku.shuffle(dset) # shuffle dataset\n",
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" y = shuffled.label\n",
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" df_1 = shuffled.drop('label', axis=1)\n",
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" shuffled = shuffled.drop('label', axis=1)['text']\n",
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" size = int(cutoff * shuffled.shape[0])\n",
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" return shuffled[:size], y[:size], shuffled[size:], y[size:]\n",
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" "
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]
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},
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{
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"cell_type": "code",
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"execution_count": 7,
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"metadata": {},
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"outputs": [],
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"source": [
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"X,y, Xt,yt = create_training_and_test_set(df_1)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 8,
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"metadata": {},
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"outputs": [],
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"source": [
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"#X2,y2, Xt2,yt2 = train_test_split(df_1['text'],df_1.label,test_size=0.3)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 9,
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"metadata": {},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"Unnamed: 0\n",
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"5507 Anthony Weiner Sends Apology Sext To Entire Cl...\n",
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"1440 John Kasich was killing it with these Iowa vot...\n",
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"3172 Yeah, yeah, with the rise of Der Trumper and t...\n",
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"6962 Vermont fights the opioid epidemic by limiting...\n",
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"6970 — Adam Baldwin (@AdamBaldwin) October 28, 2016...\n",
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"7209 Militias prepare for election unrest while Chr...\n",
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"4781 Raleigh, North Carolina (CNN) As soon as the f...\n",
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"6137 Yemen’s Hudaydah suffering from dire humanitar...\n",
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"8799 Subscribe \\nIn politics, the Third Way is a po...\n",
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"4374 Hanging in the balance is Obama’s vision of Am...\n",
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"9465 Under the Surface - Naomi Klein and the Great ...\n",
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"10409 October 28, 2016 at 9:00 PM \\nWhy would Putin ...\n",
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"2822 HAMPTON, N.H. -- Hillary Rodham Clinton said F...\n",
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"5190 (CNN) Donald Trump on Wednesday refused to say...\n",
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"2286 Gay rights won't fade as a political issue. Th...\n",
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"4308 Fox Business’s Tuesday night Republican debate...\n",
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"7305 Yes, There Are Paid Government Trolls On Socia...\n",
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"6716 Vladimir Putin: The United States continues to...\n",
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"6871 By wmw_admin on October 31, 2016 Sanchez Manni...\n",
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"8527 Banana Republic Election in the United States?...\n",
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"3658 Why are Americans expected to die sooner than ...\n",
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"9721 Comments \\nFamous techno musician Moby tore in...\n",
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"10001 Behind the headlines - conspiracies, cover-ups...\n",
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"8920 Massachusetts +11% New York +10% \\nWhen home p...\n",
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"8488 Ivana Says Young Donald Trump Was A Cry-Baby –...\n",
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"8474 Recipient Email => \\nEnemies of the United S...\n",
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"5789 Theresa May refuses to withdraw support for Sa...\n",
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"1324 Even as Hillary Clinton has stepped up her rhe...\n",
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"1744 Sally Kohn is an activist, columnist and telev...\n",
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"3887 George Washington was the first President of t...\n",
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" ... \n",
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"643 Is anyone qualified to judge The Donald?\\n\\nDo...\n",
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"6795 [Graphic: Calais street scene by Harriet Paint...\n",
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"10444 By wmw_admin on October 30, 2016 By Timothy Fi...\n",
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"8696 Unprecedented Surge In Election Fraud Incident...\n",
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"5103 The Democratic National Committee is offering ...\n",
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"8018 Comments \\nFOX News star Megyn Kelly has final...\n",
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"2896 President Obama sent a draft Authorization for...\n",
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"9188 Heseltine strangled dog as part of Thatcher ca...\n",
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"6 It's been a big week for abortion news.\\n\\nCar...\n",
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"9778 20 Foods That Naturally Unclog Arteries and Pr...\n",
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"10062 FBI Releases Files on Bill Clinton's Cash for ...\n",
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"2524 President Obama's executive action preventing ...\n",
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"8995 Rights? In The New America You Don’t Get Any R...\n",
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"8602 By Amanda Froelich For a long time, green juic...\n",
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"2886 W hen trying to explain the current unrest in ...\n",
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"3456 WASHINGTON, June 21 (Reuters) - Tensions are b...\n",
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"6564 This is how it works in the Clinton Cabal...or...\n",
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"1151 As the Democratic presidential contest reaches...\n",
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"3233 With the Department of Homeland Security’s fun...\n",
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"source": [
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"X"
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]
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{
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"cell_type": "code",
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"execution_count": 10,
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"metadata": {},
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"outputs": [],
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"source": [
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"count_vectorizer = CountVectorizer(stop_words='english')\n",
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"count_train = count_vectorizer.fit_transform(X)\n",
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"count_test = count_vectorizer.transform(Xt)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 11,
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"metadata": {},
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"outputs": [],
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"source": [
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"tfidf_vectorizer = TfidfVectorizer(stop_words='english', max_df=0.7)\n",
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"tfidf_train = tfidf_vectorizer.fit_transform(X)\n",
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"tfidf_test = tfidf_vectorizer.transform(Xt)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 12,
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"['00',\n",
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" '000',\n",
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" '0000',\n",
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" '00000031',\n",
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" '000035',\n",
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" '00006',\n",
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" '0001',\n",
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" '0001pt',\n",
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" '0002',\n",
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" '000billion']\n",
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"['حلب', 'عربي', 'عن', 'لم', 'ما', 'محاولات', 'من', 'هذا', 'والمرضى', 'ยงade']\n"
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]
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}
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],
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"source": [
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"pp(count_vectorizer.get_feature_names()[0:10])\n",
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"pp(count_vectorizer.get_feature_names()[-10:])\n"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 13,
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"['00',\n",
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" '000',\n",
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" '0000',\n",
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" '00000031',\n",
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" '000035',\n",
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" '00006',\n",
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" '0001',\n",
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" '0001pt',\n",
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" '0002',\n",
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" '000billion']\n",
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"['حلب', 'عربي', 'عن', 'لم', 'ما', 'محاولات', 'من', 'هذا', 'والمرضى', 'ยงade']\n"
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]
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}
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],
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"source": [
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"pp(tfidf_vectorizer.get_feature_names()[:10])\n",
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"pp(tfidf_vectorizer.get_feature_names()[-10:])"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 20,
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"metadata": {},
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"outputs": [],
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"source": [
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"#count_df = pd.DataFrame(count_train.A, columns=count_vectorizer.get_feature_names())\n",
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"#tfidf_df = pd.DataFrame(count_train.A, columns=tfidf_vectorizer.get_feature_names())\n",
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"#diff = set(count_df.columns) - set(tfidf_df.columns)\n",
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"#pp(count_df.equals(tfidf_df))"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 38,
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"'score: 0.8527091004734351'\n"
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]
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},
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{
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"text": [
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"Confusion matrix, without normalization\n"
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]
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}
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],
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"source": [
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||||
"clf = MultinomialNB()\n",
|
||||
"clf.fit(tfidf_train, y)\n",
|
||||
"pred = clf.predict(tfidf_test)\n",
|
||||
"score = metrics.accuracy_score(yt, pred)\n",
|
||||
"pp(\"score: \" + str(score))\n",
|
||||
"cm = metrics.confusion_matrix(yt, pred, labels=[\"FAKE\", \"REAL\"])\n",
|
||||
"plot_confusion_matrix(cm, classes=[\"FAKE\", \"REAL\"], title= \"tfidf\")"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"cut = 0.7\n",
|
||||
"\n",
|
||||
"y = df_1.label\n",
|
||||
"df_1 = df_1.drop('label', axis=1)\n"
|
||||
]
|
||||
"source": []
|
||||
}
|
||||
],
|
||||
"metadata": {
|
||||
|
||||
Loading…
Reference in New Issue
Block a user