From 1d3f49fdcc1ef633aafa98abde7642c95cb668e7 Mon Sep 17 00:00:00 2001
From: rushabh-mehta <rushabh123@gmail.com>
Date: Tue, 1 Jan 2019 08:20:12 +0000
Subject: [PATCH] Done

---
 __pycache__/__init__.cpython-36.pyc           | Bin 167 -> 168 bytes
 .../__pycache__/__init__.cpython-36.pyc       | Bin 180 -> 181 bytes
 q01_pipeline/__pycache__/build.cpython-36.pyc | Bin 1725 -> 2041 bytes
 q01_pipeline/build.py                         |  36 ++++++++++++++++++
 .../tests/__pycache__/__init__.cpython-36.pyc | Bin 186 -> 187 bytes
 .../test_q01_pipeline.cpython-36.pyc          | Bin 2014 -> 2015 bytes
 6 files changed, 36 insertions(+)

diff --git a/__pycache__/__init__.cpython-36.pyc b/__pycache__/__init__.cpython-36.pyc
index c105ea65b389830d7486c11505a8fb006d05c448..af718bfd9de7fa52558705cd088ad23ada1515b9 100644
GIT binary patch
delta 55
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delta 54
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diff --git a/q01_pipeline/__pycache__/__init__.cpython-36.pyc b/q01_pipeline/__pycache__/__init__.cpython-36.pyc
index fbce7a136c76784e20d2a9bf4114845d8d5b6a32..6802f7ca6a3430e1321400bc1fec47929312294f 100644
GIT binary patch
delta 55
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delta 54
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diff --git a/q01_pipeline/__pycache__/build.cpython-36.pyc b/q01_pipeline/__pycache__/build.cpython-36.pyc
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diff --git a/q01_pipeline/build.py b/q01_pipeline/build.py
index 96beca7..4eaaf5d 100644
--- a/q01_pipeline/build.py
+++ b/q01_pipeline/build.py
@@ -1,3 +1,4 @@
+# %load q01_pipeline/build.py
 import pandas as pd
 import numpy as np
 from sklearn.model_selection import train_test_split, GridSearchCV
@@ -5,9 +6,44 @@
 from sklearn.ensemble import RandomForestClassifier
 from sklearn.utils.class_weight import compute_class_weight
 from sklearn.metrics import roc_auc_score
+from imblearn.over_sampling import SMOTE
 
 bank = pd.read_csv('data/Bank_data_to_class.csv', sep=',')
+y = bank['y']
+X = bank.drop(['y'], axis=1)
+
+columns_to_encode = ['job','marital','education','default','housing','loan','contact','day','month','poutcome']
+lbe = LabelEncoder()
+for column  in columns_to_encode:
+    X[column] = lbe.fit_transform(X[column])
+y = lbe.fit_transform(y)
+X_train,X_test,y_train,y_test = train_test_split(X,y,test_size=0.3,random_state=9)
+model = [RandomForestClassifier()]
+
 
 # Write your solution here :
+def pipeline(X_train1,X_test1,y_trai1n,y_test1,model1):
+    bank = pd.read_csv('data/Bank_data_to_class.csv', sep=',')
+    y = bank['y']
+    X = bank.drop(['y'], axis=1)
+    columns_to_encode = ['job','marital','education','default','housing','loan','contact','day','month','poutcome']
+    lbe = LabelEncoder()
+    for column  in columns_to_encode:
+        X[column] = lbe.fit_transform(X[column])
+    y = lbe.fit_transform(y)
+    X_train,X_test,y_train,y_test = train_test_split(X,y,test_size=0.3,random_state=9)
+    smote = SMOTE(random_state=9, kind='borderline2')
+    X_sampled_train,y_sampled_train = smote.fit_sample(X_train,y_train)
+    rfc = RandomForestClassifier(class_weight={0:1,1:2},random_state=9)
+    param_grid={
+        'criterion' : ['gini','entropy'],
+        'n_estimators' : [50,75,100],
+        'max_depth' : [6,8,10],
+        'min_samples_leaf' : [10,15,20]
+    }
+    grid_search =GridSearchCV(estimator=rfc,param_grid=param_grid,cv=5)
+    grid_search.fit(X_sampled_train,y_sampled_train)
+    y_pred = grid_search.predict(X_test)
+    return grid_search,roc_auc_score(y_test,y_pred)
 
 
diff --git a/q01_pipeline/tests/__pycache__/__init__.cpython-36.pyc b/q01_pipeline/tests/__pycache__/__init__.cpython-36.pyc
index 9a74c788dfa8cb2d8c0635c15b23112acb858577..6fd03d708b37d70572b4911b489fc2652cef0e82 100644
GIT binary patch
delta 55
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diff --git a/q01_pipeline/tests/__pycache__/test_q01_pipeline.cpython-36.pyc b/q01_pipeline/tests/__pycache__/test_q01_pipeline.cpython-36.pyc
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GIT binary patch
delta 264
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