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Commit 51e152d4 authored by Jonathan Poalses's avatar Jonathan Poalses
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Added GNB, KNeighbour, and SVC ML implementations

parent 88812fda
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Showing with 36 additions and 36 deletions
nlp_gnb.ipynb
View file @ 51e152d4
...@@ -2,12 +2,12 @@ ...@@ -2,12 +2,12 @@
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...@@ -21,7 +21,7 @@ ...@@ -21,7 +21,7 @@
}, },
{ {
"cell_type": "code", "cell_type": "code",
"execution_count": 125, "execution_count": 129,
"outputs": [], "outputs": [],
"source": [ "source": [
"data = vectorizer.fit_transform(edn.loads(open(\"sample_data.txt\").read()))\n", "data = vectorizer.fit_transform(edn.loads(open(\"sample_data.txt\").read()))\n",
...@@ -30,14 +30,14 @@ ...@@ -30,14 +30,14 @@
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"outputs": [], "outputs": [],
"source": [ "source": [
"X_train, X_test, y_train, y_test = train_test_split(data, target, test_size=0.2, random_state=42)" "X_train, X_test, y_train, y_test = train_test_split(data, target, test_size=0.2, random_state=42)"
...@@ -45,14 +45,14 @@ ...@@ -45,14 +45,14 @@
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...@@ -71,8 +71,8 @@ ...@@ -71,8 +71,8 @@
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} }
......
nlp_kn.ipynb
View file @ 51e152d4
...@@ -2,12 +2,12 @@ ...@@ -2,12 +2,12 @@
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...@@ -21,7 +21,7 @@ ...@@ -21,7 +21,7 @@
}, },
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"cell_type": "code", "cell_type": "code",
"execution_count": 77, "execution_count": 81,
"outputs": [], "outputs": [],
"source": [ "source": [
"data = vectorizer.fit_transform(edn.loads(open(\"sample_data.txt\").read()))\n", "data = vectorizer.fit_transform(edn.loads(open(\"sample_data.txt\").read()))\n",
...@@ -30,14 +30,14 @@ ...@@ -30,14 +30,14 @@
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"outputs": [], "outputs": [],
"source": [ "source": [
"X_train, X_test, y_train, y_test = train_test_split(data, target, test_size=0.2, random_state=42)" "X_train, X_test, y_train, y_test = train_test_split(data, target, test_size=0.2, random_state=42)"
...@@ -45,14 +45,14 @@ ...@@ -45,14 +45,14 @@
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"outputs": [ "outputs": [
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...@@ -71,8 +71,8 @@ ...@@ -71,8 +71,8 @@
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} }
......
nlp_svc.ipynb
View file @ 51e152d4
...@@ -2,12 +2,12 @@ ...@@ -2,12 +2,12 @@
"cells": [ "cells": [
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"outputs": [], "outputs": [],
...@@ -21,7 +21,7 @@ ...@@ -21,7 +21,7 @@
}, },
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"cell_type": "code", "cell_type": "code",
"execution_count": 462, "execution_count": 470,
"outputs": [], "outputs": [],
"source": [ "source": [
"data = vectorizer.fit_transform(edn.loads(open(\"sample_data.txt\").read()))\n", "data = vectorizer.fit_transform(edn.loads(open(\"sample_data.txt\").read()))\n",
...@@ -30,14 +30,14 @@ ...@@ -30,14 +30,14 @@
"metadata": { "metadata": {
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{ {
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"outputs": [], "outputs": [],
"source": [ "source": [
"X_train, X_test, y_train, y_test = train_test_split(data, target, test_size=0.2, random_state=42)" "X_train, X_test, y_train, y_test = train_test_split(data, target, test_size=0.2, random_state=42)"
...@@ -45,14 +45,14 @@ ...@@ -45,14 +45,14 @@
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"outputs": [ "outputs": [
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"name": "stdout", "name": "stdout",
...@@ -71,8 +71,8 @@ ...@@ -71,8 +71,8 @@
"metadata": { "metadata": {
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} }
......
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