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Naivebayes exercicio #69

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9f74d59
Adding knn-exercicio
joelRibe Dec 19, 2017
57f974b
Adding Naive_Bayes Exercício
joelRibe Dec 19, 2017
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2 changes: 1 addition & 1 deletion 2017/03-classificacao-scikit-learn/hands-on-knn.ipynb
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Original file line number Diff line number Diff line change
Expand Up @@ -514,7 +514,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.6.2"
"version": "3.6.1"
}
},
"nbformat": 4,
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318 changes: 318 additions & 0 deletions 2017/04-knn-exercicio/knn_joel_ribeiro.ipynb
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892 changes: 892 additions & 0 deletions 2017/04-knn-exercicio/train.csv
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30 changes: 22 additions & 8 deletions 2017/05-naive-bayes/Naive_Bayes_Francisco_Carlos.ipynb
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Original file line number Diff line number Diff line change
Expand Up @@ -167,7 +167,9 @@
{
"cell_type": "code",
"execution_count": 535,
"metadata": {},
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"#Separa em conjunto de treino (70%) e teste (30%)\n",
Expand All @@ -181,7 +183,9 @@
{
"cell_type": "code",
"execution_count": 536,
"metadata": {},
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"#separa conjunto de teste em features e classe e calcula o tamanho total de treino\n",
Expand Down Expand Up @@ -535,7 +539,9 @@
{
"cell_type": "code",
"execution_count": 546,
"metadata": {},
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"#feature_index = [(frequency_label.loc[i] == data.loc[i]).argmax() for i in data.index]\n",
Expand All @@ -545,7 +551,9 @@
{
"cell_type": "code",
"execution_count": 547,
"metadata": {},
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"#Faz a predição do conjunto de teste\n",
Expand All @@ -569,7 +577,9 @@
{
"cell_type": "code",
"execution_count": 548,
"metadata": {},
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"result_y = np.squeeze(np.asarray(predicts))\n",
Expand Down Expand Up @@ -644,7 +654,9 @@
{
"cell_type": "code",
"execution_count": 552,
"metadata": {},
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"#Transforma os valores string em númericos\n",
Expand All @@ -666,7 +678,9 @@
{
"cell_type": "code",
"execution_count": 553,
"metadata": {},
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"#Faz o fit e o predict com a implementação do scikit\n",
Expand Down Expand Up @@ -787,7 +801,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.6.3"
"version": "3.6.1"
}
},
"nbformat": 4,
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