From 3348346dfb5fa143bf69403c18c0e6403efd2127 Mon Sep 17 00:00:00 2001
From: rajeshbrid <rajesh_brid@hotmail.com>
Date: Thu, 25 Oct 2018 04:13:14 +0000
Subject: [PATCH 1/4] Done

---
 __pycache__/__init__.cpython-36.pyc           | Bin 0 -> 148 bytes
 .../__pycache__/__init__.cpython-36.pyc       | Bin 0 -> 174 bytes
 .../__pycache__/build.cpython-36.pyc          | Bin 0 -> 1145 bytes
 q01_my_decision_regressor/build.py            |  27 +++++++++++++++---
 .../tests/__pycache__/__init__.cpython-36.pyc | Bin 0 -> 180 bytes
 ...t_q01_my_decision_regressor.cpython-36.pyc | Bin 0 -> 2991 bytes
 6 files changed, 23 insertions(+), 4 deletions(-)
 create mode 100644 __pycache__/__init__.cpython-36.pyc
 create mode 100644 q01_my_decision_regressor/__pycache__/__init__.cpython-36.pyc
 create mode 100644 q01_my_decision_regressor/__pycache__/build.cpython-36.pyc
 create mode 100644 q01_my_decision_regressor/tests/__pycache__/__init__.cpython-36.pyc
 create mode 100644 q01_my_decision_regressor/tests/__pycache__/test_q01_my_decision_regressor.cpython-36.pyc

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diff --git a/q01_my_decision_regressor/build.py b/q01_my_decision_regressor/build.py
index 5eb1927..a4287e1 100644
--- a/q01_my_decision_regressor/build.py
+++ b/q01_my_decision_regressor/build.py
@@ -1,3 +1,4 @@
+# %load q01_my_decision_regressor/build.py
 # default imports
 from sklearn.model_selection import GridSearchCV
 from sklearn.tree import DecisionTreeRegressor
@@ -5,13 +6,31 @@
 from sklearn.model_selection import train_test_split
 import pandas as pd
 
-data = pd.read_csv("./data/house_pricing.csv")
+data = pd.read_csv('./data/house_pricing.csv')
 X = data.iloc[:, :-1]
 y = data.iloc[:, -1]
 X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.3, random_state=9)
 
-param_grid = {"max_depth": [2, 3, 5, 6, 8, 10, 15, 20, 30, 50],
-              "max_leaf_nodes": [2, 3, 4, 5, 10, 15, 20],
-              "max_features": [4, 8, 20, 25]}
+param_grid = {'max_depth': [2, 3, 5, 6, 8, 10, 15, 20, 30, 50],
+              'max_leaf_nodes': [2, 3, 4, 5, 10, 15, 20],
+              'max_features': [4, 8, 20, 25]}
 
 # Write your solution here :
+
+def my_decision_regressor(X_train, X_test, y_train, y_test,param_grid):
+    dt = DecisionTreeRegressor(random_state=9)
+    grid_search = GridSearchCV(estimator = dt, param_grid=param_grid,cv=5)
+    model  = grid_search.fit(X_train,y_train)
+    y_pred = model.predict(X_test)
+    
+    best_params = model.best_params_
+    r_square    = r2_score(y_test,y_pred)
+    
+    # print (r_square, best_params)
+    
+    return r_square, best_params
+
+# my_decision_regressor(X_train, X_test, y_train, y_test,param_grid)
+
+
+
diff --git a/q01_my_decision_regressor/tests/__pycache__/__init__.cpython-36.pyc b/q01_my_decision_regressor/tests/__pycache__/__init__.cpython-36.pyc
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From c6780e8829dfc0f94949b152c18b5d582cab2800 Mon Sep 17 00:00:00 2001
From: rajeshbrid <rajesh_brid@hotmail.com>
Date: Thu, 25 Oct 2018 04:16:23 +0000
Subject: [PATCH 2/4] Done

---
 .../__pycache__/__init__.cpython-36.pyc       | Bin 0 -> 176 bytes
 .../__pycache__/build.cpython-36.pyc          | Bin 0 -> 1247 bytes
 q02_decision_regressor_plot/build.py          |  23 +++++++++++++++++-
 .../tests/__pycache__/__init__.cpython-36.pyc | Bin 0 -> 182 bytes
 ...q02_decision_regressor_plot.cpython-36.pyc | Bin 0 -> 1135 bytes
 5 files changed, 22 insertions(+), 1 deletion(-)
 create mode 100644 q02_decision_regressor_plot/__pycache__/__init__.cpython-36.pyc
 create mode 100644 q02_decision_regressor_plot/__pycache__/build.cpython-36.pyc
 create mode 100644 q02_decision_regressor_plot/tests/__pycache__/__init__.cpython-36.pyc
 create mode 100644 q02_decision_regressor_plot/tests/__pycache__/test_q02_decision_regressor_plot.cpython-36.pyc

diff --git a/q02_decision_regressor_plot/__pycache__/__init__.cpython-36.pyc b/q02_decision_regressor_plot/__pycache__/__init__.cpython-36.pyc
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diff --git a/q02_decision_regressor_plot/build.py b/q02_decision_regressor_plot/build.py
index 020d81e..1552513 100644
--- a/q02_decision_regressor_plot/build.py
+++ b/q02_decision_regressor_plot/build.py
@@ -1,3 +1,4 @@
+# %load q02_decision_regressor_plot/build.py
 # default imports
 from sklearn.model_selection import train_test_split
 from sklearn.tree import DecisionTreeRegressor
@@ -7,7 +8,7 @@
 import numpy as np
 plt.switch_backend('agg')
 
-data = pd.read_csv("./data/house_pricing.csv")
+data = pd.read_csv('./data/house_pricing.csv')
 X = data.iloc[:, :-1]
 y = data.iloc[:, -1]
 X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.3, random_state=9)
@@ -15,3 +16,23 @@
 depth_list = [2, 8, 10, 15, 20, 25, 30, 35, 45, 50, 80]
 
 # Write your solution here :
+
+def decision_regressor_plot(X_train, X_test, y_train, y_test,depth_list):
+    mse_listTrain=list()
+    mse_listTest=list()
+    for i in depth_list:
+        dt = DecisionTreeRegressor(criterion='mse',max_depth=i,random_state=9)
+        model = dt.fit(X_train,y_train)
+        y_predTrain = model.predict(X_train)
+        mse_listTrain.append(mean_squared_error(y_train,y_predTrain))
+        y_predTest = model.predict(X_test)
+        mse_listTest.append(mean_squared_error(y_test,y_predTest))
+        
+    plt.plot(depth_list,mse_listTrain)
+    plt.plot(depth_list,mse_listTest)
+    plt.show();
+    
+# decision_regressor_plot(X_train, X_test, y_train, y_test,depth_list)
+
+
+
diff --git a/q02_decision_regressor_plot/tests/__pycache__/__init__.cpython-36.pyc b/q02_decision_regressor_plot/tests/__pycache__/__init__.cpython-36.pyc
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From e7e68800218ad3048a37615281a7e42c9db5d56d Mon Sep 17 00:00:00 2001
From: rajeshbrid <rajesh_brid@hotmail.com>
Date: Fri, 2 Nov 2018 03:40:43 +0000
Subject: [PATCH 3/4] Done

---
 .../__pycache__/__init__.cpython-36.pyc       | Bin 0 -> 175 bytes
 .../__pycache__/build.cpython-36.pyc          | Bin 0 -> 1208 bytes
 q03_my_decision_classifier/build.py           |  26 ++++++++++++++----
 .../tests/__pycache__/__init__.cpython-36.pyc | Bin 0 -> 181 bytes
 ..._q03_my_decision_classifier.cpython-36.pyc | Bin 0 -> 3027 bytes
 5 files changed, 21 insertions(+), 5 deletions(-)
 create mode 100644 q03_my_decision_classifier/__pycache__/__init__.cpython-36.pyc
 create mode 100644 q03_my_decision_classifier/__pycache__/build.cpython-36.pyc
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 create mode 100644 q03_my_decision_classifier/tests/__pycache__/test_q03_my_decision_classifier.cpython-36.pyc

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diff --git a/q03_my_decision_classifier/build.py b/q03_my_decision_classifier/build.py
index 73c9856..a06b932 100644
--- a/q03_my_decision_classifier/build.py
+++ b/q03_my_decision_classifier/build.py
@@ -1,3 +1,4 @@
+# %load q03_my_decision_classifier/build.py
 # default imports
 from sklearn.model_selection import RandomizedSearchCV
 from sklearn.tree import DecisionTreeClassifier
@@ -6,16 +7,31 @@
 import pandas as pd
 import numpy as np
 
-data = pd.read_csv("./data/loan_prediction.csv")
+data = pd.read_csv('./data/loan_prediction.csv')
 np.random.seed(9)
 X = data.iloc[:, :-1]
 y = data.iloc[:, -1]
 X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.3, random_state=9)
 
-param_grid = {"max_depth": [8, 10, 15, 20],
-              "max_leaf_nodes": [2, 5, 9, 15, 20],
-              "max_features": [1, 2, 3, 5]}
-
+param_grid = {'max_depth': [8, 10, 15, 20],
+              'max_leaf_nodes': [2, 5, 9, 15, 20],
+              'max_features': [1, 2, 3, 5]}
 
 # Write your solution here :
 
+def my_decision_classifier (X_train, X_test, y_train, y_test,param_grid,n_iter_search=10):
+    dt = DecisionTreeClassifier(random_state=9)
+    ran_search = RandomizedSearchCV(estimator = dt, param_distributions=param_grid,n_iter=n_iter_search)
+    model = ran_search.fit(X_train,y_train)
+    y_pred = model.predict(X_test)
+    
+    best_params=model.best_params_
+    accuracy = accuracy_score(y_test,y_pred)
+    # print (accuracy, best_params)
+              
+    return accuracy, best_params
+
+# my_decision_classifier (X_train, X_test, y_train, y_test,param_grid,n_iter_search=10)
+
+
+
diff --git a/q03_my_decision_classifier/tests/__pycache__/__init__.cpython-36.pyc b/q03_my_decision_classifier/tests/__pycache__/__init__.cpython-36.pyc
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From 25148194034ebf1d6b48074bfc1e7689c8f37094 Mon Sep 17 00:00:00 2001
From: rajeshbrid <rajesh_brid@hotmail.com>
Date: Fri, 2 Nov 2018 03:42:52 +0000
Subject: [PATCH 4/4] Done

---
 .../__pycache__/__init__.cpython-36.pyc       | Bin 0 -> 177 bytes
 .../__pycache__/build.cpython-36.pyc          | Bin 0 -> 1292 bytes
 q04_decision_classifier_plot/build.py         |  26 ++++++++++++++++--
 .../tests/__pycache__/__init__.cpython-36.pyc | Bin 0 -> 183 bytes
 ...04_decision_classifier_plot.cpython-36.pyc | Bin 0 -> 1145 bytes
 5 files changed, 24 insertions(+), 2 deletions(-)
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 create mode 100644 q04_decision_classifier_plot/__pycache__/build.cpython-36.pyc
 create mode 100644 q04_decision_classifier_plot/tests/__pycache__/__init__.cpython-36.pyc
 create mode 100644 q04_decision_classifier_plot/tests/__pycache__/test_q04_decision_classifier_plot.cpython-36.pyc

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diff --git a/q04_decision_classifier_plot/build.py b/q04_decision_classifier_plot/build.py
index 44e9e87..40cf33f 100644
--- a/q04_decision_classifier_plot/build.py
+++ b/q04_decision_classifier_plot/build.py
@@ -1,3 +1,4 @@
+# %load q04_decision_classifier_plot/build.py
 # default imports
 from sklearn.model_selection import RandomizedSearchCV
 from sklearn.tree import DecisionTreeClassifier
@@ -8,7 +9,7 @@
 import numpy as np
 plt.switch_backend('agg')
 
-data = pd.read_csv("./data/loan_prediction.csv")
+data = pd.read_csv('./data/loan_prediction.csv')
 np.random.seed(9)
 X = data.iloc[:, :-1]
 y = data.iloc[:, -1]
@@ -16,5 +17,26 @@
 
 depth_list = [8, 10, 15, 20, 50, 100, 120, 150, 175, 200]
 
-
 # Write your solution here :
+
+def decision_classifier_plot(X_train, X_test, y_train, y_test,depth_list):
+    mse_listTrain=list()
+    mse_listTest=list()
+    for i in depth_list:
+        dt = DecisionTreeClassifier(max_depth=i,random_state=9)
+        model = dt.fit(X_train,y_train)
+        
+        y_predTrain = model.predict(X_train)
+        mse_listTrain.append(accuracy_score(y_train,y_predTrain))
+        
+        y_predTest = model.predict(X_test)
+        mse_listTest.append(accuracy_score(y_test,y_predTest))
+        
+    plt.plot(depth_list,mse_listTrain)
+    plt.plot(depth_list,mse_listTest)
+    plt.show()
+    
+# decision_classifier_plot(X_train, X_test, y_train, y_test,depth_list)
+
+
+
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