From 3d31fbb82620c7f5275b89769ca44f6b002df505 Mon Sep 17 00:00:00 2001
From: Sakshi-BUK <sakshi.dhokrat96@gmail.com>
Date: Tue, 14 Nov 2017 05:56:31 +0000
Subject: [PATCH] Done

---
 __init__.pyc                             | Bin 180 -> 169 bytes
 q01_pipeline/__init__.pyc                | Bin 193 -> 182 bytes
 q01_pipeline/build.py                    |  25 ++++++++++++++++++++++-
 q01_pipeline/build.pyc                   | Bin 2322 -> 1888 bytes
 q01_pipeline/tests/__init__.pyc          | Bin 199 -> 188 bytes
 q01_pipeline/tests/test_q01_pipeline.pyc | Bin 2221 -> 2086 bytes
 6 files changed, 24 insertions(+), 1 deletion(-)

diff --git a/__init__.pyc b/__init__.pyc
index d1c94d3c52cde5a38567928948231f3d1adc4dec..e6467ddd0136c2eea7617190e6aff725aea78554 100644
GIT binary patch
delta 61
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delta 72
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diff --git a/q01_pipeline/__init__.pyc b/q01_pipeline/__init__.pyc
index b360a57252ba2db1b27d2b2e17e906e3f57cb43b..6895574218758a06ce638c9d9d64f4ff435f4c9f 100644
GIT binary patch
delta 74
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diff --git a/q01_pipeline/build.py b/q01_pipeline/build.py
index 96beca7..15ff46e 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
@@ -7,7 +8,29 @@
 from sklearn.metrics import roc_auc_score
 
 bank = pd.read_csv('data/Bank_data_to_class.csv', sep=',')
-
+model=RandomForestClassifier(random_state=9,class_weight='balanced')
 # Write your solution here :
+y=bank['y']
+X=bank.drop(['y'],axis=1)
+X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.3, random_state=9)
 
+def pipeline(X_train, X_test, y_train, y_test,model):
+    param_grid={'max_depth':[2,3,5,6,8,10,15,20,30],'max_leaf_nodes':[2,5,10,15,20],
+            'max_features':[8,10,12,14]}
+    grid=GridSearchCV(estimator=model,param_grid=param_grid)
+    label=LabelEncoder()
+    y_train=label.fit_transform(y_train)
+    for column in X_train.columns:
+        if X_train[column].dtype==type(object):
+            label=LabelEncoder()
+            X_train[column]=label.fit_transform(X_train[column])
+    y_test=label.fit_transform(y_test)
+    for column in X_test.columns:
+        if X_test[column].dtype==type(object):
+            label=LabelEncoder()
+            X_test[column]=label.fit_transform(X_test[column])
+    grid.fit(X_train,y_train)
+    auc=roc_auc_score(y_test,grid.predict(X_test))
+    return grid.fit(X_train,y_train),auc
 
+#pipeline(X_train, X_test, y_train, y_test,model)
diff --git a/q01_pipeline/build.pyc b/q01_pipeline/build.pyc
index 5a9b3ad55dc3cef2130ad4675212f4c1bab540ed..55c611a1a25a40fe770380c2b43eecea712f9e79 100644
GIT binary patch
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diff --git a/q01_pipeline/tests/__init__.pyc b/q01_pipeline/tests/__init__.pyc
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diff --git a/q01_pipeline/tests/test_q01_pipeline.pyc b/q01_pipeline/tests/test_q01_pipeline.pyc
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