From c4e8a48870dd937a509386dcfba4f757885e618a Mon Sep 17 00:00:00 2001
From: Vagus30 <vishwas.tejaswi@gmail.com>
Date: Tue, 28 Aug 2018 21:13:47 +0000
Subject: [PATCH 1/2] Done

---
 __pycache__/__init__.cpython-36.pyc              | Bin 0 -> 149 bytes
 q01_bagging/__pycache__/__init__.cpython-36.pyc  | Bin 0 -> 161 bytes
 q01_bagging/__pycache__/build.cpython-36.pyc     | Bin 0 -> 1054 bytes
 q01_bagging/build.py                             |   8 ++++++++
 .../tests/__pycache__/__init__.cpython-36.pyc    | Bin 0 -> 167 bytes
 .../__pycache__/test_q01_bagging.cpython-36.pyc  | Bin 0 -> 958 bytes
 6 files changed, 8 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

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diff --git a/q01_bagging/__pycache__/__init__.cpython-36.pyc b/q01_bagging/__pycache__/__init__.cpython-36.pyc
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diff --git a/q01_bagging/build.py b/q01_bagging/build.py
index 19f8726..a592b3d 100644
--- a/q01_bagging/build.py
+++ b/q01_bagging/build.py
@@ -1,3 +1,4 @@
+# %load q01_bagging/build.py
 import pandas as pd
 from sklearn.model_selection import train_test_split
 from sklearn.tree import DecisionTreeClassifier
@@ -15,5 +16,12 @@
 
 
 # Write your code here
+def bagging(X_train, X_test, y_train, y_test,n_est):
+    clf = BaggingClassifier(DecisionTreeClassifier(),n_estimators=50,max_sample=0.67,bootstrap=True,random_state=9)
+    clf.fit(X_train,y_train)
+    y_pred = clf.predict(X_test)
+    score = accuracy_score(y_test,y_pred)
+    plt.plot(n_est,score)
+    plt.show()
 
 
diff --git a/q01_bagging/tests/__pycache__/__init__.cpython-36.pyc b/q01_bagging/tests/__pycache__/__init__.cpython-36.pyc
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From 55fff8f4d876ea6e29713f282c24025b97d2593d Mon Sep 17 00:00:00 2001
From: Vagus30 <vishwas.tejaswi@gmail.com>
Date: Tue, 28 Aug 2018 22:11:16 +0000
Subject: [PATCH 2/2] Done

---
 .../__pycache__/__init__.cpython-36.pyc       | Bin 0 -> 166 bytes
 .../__pycache__/build.cpython-36.pyc          | Bin 0 -> 1592 bytes
 q02_stacking_clf/build.py                     |  30 ++++++++++++++++++
 .../tests/__pycache__/__init__.cpython-36.pyc | Bin 0 -> 172 bytes
 .../test_q02_stacking_clf.cpython-36.pyc      | Bin 0 -> 2380 bytes
 5 files changed, 30 insertions(+)
 create mode 100644 q02_stacking_clf/__pycache__/__init__.cpython-36.pyc
 create mode 100644 q02_stacking_clf/__pycache__/build.cpython-36.pyc
 create mode 100644 q02_stacking_clf/tests/__pycache__/__init__.cpython-36.pyc
 create mode 100644 q02_stacking_clf/tests/__pycache__/test_q02_stacking_clf.cpython-36.pyc

diff --git a/q02_stacking_clf/__pycache__/__init__.cpython-36.pyc b/q02_stacking_clf/__pycache__/__init__.cpython-36.pyc
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diff --git a/q02_stacking_clf/__pycache__/build.cpython-36.pyc b/q02_stacking_clf/__pycache__/build.cpython-36.pyc
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diff --git a/q02_stacking_clf/build.py b/q02_stacking_clf/build.py
index 7b1c5f8..7e3833d 100644
--- a/q02_stacking_clf/build.py
+++ b/q02_stacking_clf/build.py
@@ -1,4 +1,6 @@
+# %load q02_stacking_clf/build.py
 # Default imports
+from mlxtend.classifier import StackingClassifier
 from sklearn.model_selection import train_test_split
 from sklearn.tree import DecisionTreeClassifier
 from sklearn.linear_model import LogisticRegression
@@ -15,4 +17,32 @@
 X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.3, random_state=9)
 
 # Write your code here
+clf1 = LogisticRegression(random_state=9)
+clf2 = DecisionTreeClassifier(random_state=9)
+clf3 = DecisionTreeClassifier(max_depth=9, random_state=9)
+
+bagging_clf1 = BaggingClassifier(clf2, n_estimators=100, max_samples=100,
+                                 bootstrap=True, random_state=9, oob_score=True)
+bagging_clf2 = BaggingClassifier(clf1, n_estimators=100, max_samples=100,
+                                 bootstrap=True, random_state=9, oob_score=True)
+bagging_clf3 = BaggingClassifier(clf3, n_estimators=100, max_samples=100,
+                                 bootstrap=True, random_state=9, oob_score=True)
+
+model = [bagging_clf1, bagging_clf2, bagging_clf3]
+def stacking_clf(model, X_train, y_train, X_test, y_test):
+    predictions = []
+    for i in model:
+        i.fit(X_train, y_train)
+        pred = np.array(i.predict_proba(X_train))
+        predictions.append(pred)
+    X_bag_train = np.concatenate((predictions[0], predictions[1], predictions[2]), axis=1)
+    predictions_test = []
+    for j in model:
+        pred = np.array(j.predict_proba(X_test))
+        predictions_test.append(pred)
+    X_bag_test = np.concatenate((predictions_test[0], predictions_test[1], predictions_test[2]), axis=1)
+    predictions_bag_final = clf1.fit(X_bag_train, y_train).predict(X_bag_test)
+    return accuracy_score(y_test, predictions_bag_final)
+    
+
 
diff --git a/q02_stacking_clf/tests/__pycache__/__init__.cpython-36.pyc b/q02_stacking_clf/tests/__pycache__/__init__.cpython-36.pyc
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