From 4b1799e420ca45c53bc9089fd0208d62cf496896 Mon Sep 17 00:00:00 2001
From: Sumeshks29 <sumeshks29@gmail.com>
Date: Sat, 27 Oct 2018 14:32:49 +0000
Subject: [PATCH] Done

---
 __pycache__/__init__.cpython-36.pyc           | Bin 0 -> 152 bytes
 .../__pycache__/__init__.cpython-36.pyc       | Bin 0 -> 164 bytes
 q01_bagging/__pycache__/build.cpython-36.pyc  | Bin 0 -> 1373 bytes
 q01_bagging/build.py                          |  26 ++++++++++++++++++
 .../tests/__pycache__/__init__.cpython-36.pyc | Bin 0 -> 170 bytes
 .../test_q01_bagging.cpython-36.pyc           | Bin 0 -> 961 bytes
 6 files changed, 26 insertions(+)
 create mode 100644 __pycache__/__init__.cpython-36.pyc
 create mode 100644 q01_bagging/__pycache__/__init__.cpython-36.pyc
 create mode 100644 q01_bagging/__pycache__/build.cpython-36.pyc
 create mode 100644 q01_bagging/tests/__pycache__/__init__.cpython-36.pyc
 create mode 100644 q01_bagging/tests/__pycache__/test_q01_bagging.cpython-36.pyc

diff --git a/__pycache__/__init__.cpython-36.pyc b/__pycache__/__init__.cpython-36.pyc
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diff --git a/q01_bagging/build.py b/q01_bagging/build.py
index 19f8726..ec1cb62 100644
--- a/q01_bagging/build.py
+++ b/q01_bagging/build.py
@@ -1,4 +1,6 @@
+# %load q01_bagging/build.py
 import pandas as pd
+import numpy as np
 from sklearn.model_selection import train_test_split
 from sklearn.tree import DecisionTreeClassifier
 from sklearn.ensemble import BaggingClassifier
@@ -15,5 +17,29 @@
 
 
 # Write your code here
+def bagging(X_train, X_test, y_train, y_test, n_est):
+    
+    i=1
+    dict1=dict()
+    dict2=dict()
+    
+    while (i<=50):        
+        # Fitting bagging classifier with Logisitc Regression
+        bagging_clf2 = BaggingClassifier(DecisionTreeClassifier(), n_estimators=i, max_samples=0.67, 
+                                        bootstrap=True, random_state=9,max_features=0.67)
 
+        bagging_clf2.fit(X_train, y_train)
+        y_pred_train = bagging_clf2.predict(X_train)
+        score_bc_dt_t = accuracy_score(y_train, y_pred_train)
+        y_pred_test = bagging_clf2.predict(X_test)
+        score_bc_dt = accuracy_score(y_test, y_pred_test)
+        dict1[i]=score_bc_dt_t
+        dict2[i]=score_bc_dt
+        i+=1
+    
+    plt.plot(np.arange(1,51),dict1.values())
+    plt.plot(np.arange(1,51),dict2.values())
+    print(plt.show())
+
+bagging(X_train, X_test, y_train, y_test, n_est = 51)
 
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