From a66f874214f4cf96647aca96bd20b1111f23f91a Mon Sep 17 00:00:00 2001
From: HardikaB <hardi.2607@gmail.com>
Date: Tue, 28 Aug 2018 11:08:53 +0000
Subject: [PATCH] Done

---
 __pycache__/__init__.cpython-36.pyc           | Bin 135 -> 146 bytes
 .../__pycache__/__init__.cpython-36.pyc       | Bin 151 -> 162 bytes
 .../__pycache__/build.cpython-36.pyc          | Bin 794 -> 1425 bytes
 q01_grid_search/build.py                      |  32 ++++++++++++++----
 .../tests/__pycache__/__init__.cpython-36.pyc | Bin 157 -> 168 bytes
 .../test_q01_grid_search.cpython-36.pyc       | Bin 3729 -> 3739 bytes
 q02_fit/__pycache__/__init__.cpython-36.pyc   | Bin 143 -> 154 bytes
 q02_fit/__pycache__/build.cpython-36.pyc      | Bin 1004 -> 1258 bytes
 q02_fit/build.py                              |  17 +++++++---
 .../tests/__pycache__/__init__.cpython-36.pyc | Bin 149 -> 160 bytes
 .../__pycache__/test_q02_fit.cpython-36.pyc   | Bin 2641 -> 2652 bytes
 11 files changed, 38 insertions(+), 11 deletions(-)

diff --git a/__pycache__/__init__.cpython-36.pyc b/__pycache__/__init__.cpython-36.pyc
index 14812de5bbb2a004d139995a9d5f098ae50a00f5..7974dcf317d72bbd8759d07cb0b305064dc3b353 100644
GIT binary patch
delta 49
zcmZo?oW#g(%*)HwsUAI%-9pY@KO;XkRo^4AC?zvH(Mdl%zbL!7ATc>rKRG`obz+by
E09IiSZvX%Q

delta 38
tcmbQl*v`mq%*)HQxLAH7yM?fcenx(7s(wjoaf!Z5YH@Z+e!;|8Qvk<63%LLQ

diff --git a/q01_grid_search/__pycache__/__init__.cpython-36.pyc b/q01_grid_search/__pycache__/__init__.cpython-36.pyc
index 9413fbb035692cba6960d05692dfdb9b5cbb7e65..9c7853637d4e6e71d7b566fe4389782a6e231750 100644
GIT binary patch
delta 49
zcmbQvxQLP6n3tEUQ$2bjyM>&;enx(7s=h~JQA%cZqLY4jeo=ODL1J>MesX?F>ck*d
E0A7I)uK)l5

delta 38
tcmZ3)IGvH*n3tDpak2bFb_-z_{fzwFRQ;0F;u3wA)Z*-t{DO(Gt^mzY3;6&5

diff --git a/q01_grid_search/__pycache__/build.cpython-36.pyc b/q01_grid_search/__pycache__/build.cpython-36.pyc
index dbd3e7a28645ede9c396ea197ab2e742dc768ea0..74bd9f04b6f8450405f932144c0d8843c1762535 100644
GIT binary patch
delta 951
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delta 328
zcmbQpJ&R4*n3tDpaj|^#TqXvF#|%h-4ajx?;^Ivcl^yF-nX@=k*qRxmxKg>YxKkKY
z7+aZuq*yCc8j~bL6c3W9I9P-?l{J+ol{bYWg)@b#mnDWJiZ6;kN+3!wg*$~Og*Tl!
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R2r_XoiZKc?NdWmE2mrf_QfmMJ

diff --git a/q01_grid_search/build.py b/q01_grid_search/build.py
index 20c99a1..004c08c 100644
--- a/q01_grid_search/build.py
+++ b/q01_grid_search/build.py
@@ -1,22 +1,42 @@
+# %load q01_grid_search/build.py
 # Default imports
 
 import warnings
-warnings.filterwarnings("ignore")
+warnings.filterwarnings('ignore')
 import pandas as pd
 from sklearn.model_selection import train_test_split
 from sklearn.ensemble import RandomForestClassifier
 from sklearn.model_selection import GridSearchCV
+import numpy as np
+from sklearn.metrics import accuracy_score, roc_auc_score, make_scorer
 
 loan_data = pd.read_csv('data/loan_prediction.csv')
 X_bal = loan_data.iloc[:, :-1]
 y_bal = loan_data.iloc[:, -1]
 
 X_train, X_test, y_train, y_test = train_test_split(X_bal, y_bal, test_size=0.33, random_state=9)
-param_grid = {"max_features": ['sqrt', 4, "log2"],
-              "n_estimators": [10, 50, 120],
-              "max_depth": [40, 20, 10],
-              "max_leaf_nodes": [5, 10, 2]}
-
+param_grid = {'max_features': ['sqrt', 4, 'log2'],
+              'n_estimators': [10, 50, 120],
+              'max_depth': [40, 20, 10],
+              'max_leaf_nodes': [5, 10, 2]}
+rfc = RandomForestClassifier(oob_score=True, random_state=9)
 
 # Write your solution here :
+def grid_search(X_train,y_train,model, param_grid,cv=3):      
+    clf = model
+    np.random.seed(9)
+    parameters = param_grid
+    acc_scorer = make_scorer(accuracy_score)
+    
+    # Run the grid search
+    grid_obj = GridSearchCV(clf, param_grid, scoring=acc_scorer)
+    grid_obj = grid_obj.fit(X_train, y_train)
+    variable1=list()
+    variable3=list()
+    for i in grid_obj.grid_scores_:
+        variable1.append(i[0])
+        variable3.append(i[1])
+    variable2=np.array(variable3)
+    return grid_obj,variable1,variable2
+
 
diff --git a/q01_grid_search/tests/__pycache__/__init__.cpython-36.pyc b/q01_grid_search/tests/__pycache__/__init__.cpython-36.pyc
index 5cb0753554300b5c4d0de098c675c24f802d7273..4e919b8dc83875674f8290cb260fe170dcf750dd 100644
GIT binary patch
delta 49
zcmbQsxPp=0n3tEUOFeobyM<h+enx(7s=h~JQA%cZqLY4jeo=ODL1J>MesX?F>ck*#
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delta 38
tcmZ3%IG2&#n3tDpak2bFb_-!I{fzwFRQ;0F;u3wA)Z*-t{DO(G-T=>*3=seT

diff --git a/q01_grid_search/tests/__pycache__/test_q01_grid_search.cpython-36.pyc b/q01_grid_search/tests/__pycache__/test_q01_grid_search.cpython-36.pyc
index 6061f23a0ca786fa4210816073f732a59b5c5681..f4ac32645c445015a32c0ef69276d1ad5450c370 100644
GIT binary patch
delta 70
zcmbOzJ6o31n3tEUOFcSz<3`SOX1PTDjQreGeUHSVl+5fzC;jmJqU_>=#N<@{<ouM>
a&CSfa7#W=>C$ed<<YX3?Y|ds?;{*T`+7^=l

delta 64
zcmbO&J5iR?n3tF9U9o)hrj4BG%)(*%8Tq-X`X#BwCHgL@#n~nK1)KYrcQG=$OwMN0
UU@a*v$Vr{NfK6g^FDoA>0H)s*{Qv*}

diff --git a/q02_fit/__pycache__/__init__.cpython-36.pyc b/q02_fit/__pycache__/__init__.cpython-36.pyc
index 7d3ab2600f447b3e60420a4a5f073ee9b922a988..a45bba55b165c8a0d517d1d8e11e552de9c27482 100644
GIT binary patch
delta 49
zcmeBYoW;m)%*)HwsUAI%-9pY?KO;XkRo^4AC?zvH(Mdl%zbL!7ATc>rKRG`obz+b$
E09tVmj{pDw

delta 38
tcmbQm*w4sr%*)HQxLAH7yM?fgenx(7s(wjoaf!Z5YH@Z+e!;|8TL8*P3)uhw

diff --git a/q02_fit/__pycache__/build.cpython-36.pyc b/q02_fit/__pycache__/build.cpython-36.pyc
index 87b27857062246070d7ade7c600fbb5b62693efa..1bd0da4999641d7e63656434cd0b6d48d0b53ebe 100644
GIT binary patch
delta 582
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delta 347
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diff --git a/q02_fit/build.py b/q02_fit/build.py
index fbafb1a..f99b195 100644
--- a/q02_fit/build.py
+++ b/q02_fit/build.py
@@ -1,3 +1,4 @@
+# %load q02_fit/build.py
 # Default imports
 
 import pandas as pd
@@ -5,6 +6,7 @@
 from sklearn.metrics import confusion_matrix, accuracy_score, classification_report
 from sklearn.model_selection import train_test_split
 from sklearn.ensemble import RandomForestClassifier
+import numpy as np
 
 
 loan_data = pd.read_csv('data/loan_prediction.csv')
@@ -13,15 +15,20 @@
 
 X_train, X_test, y_train, y_test = train_test_split(X_bal, y_bal, test_size=0.33, random_state=9)
 rfc = RandomForestClassifier(oob_score=True, random_state=9)
-param_grid = {"max_features": ['sqrt', 4, "log2"],
-              "n_estimators": [10, 50, 120],
-              "max_depth": [40, 20, 10],
-              "max_leaf_nodes": [5, 10, 2]}
+param_grid = {'max_features': ['sqrt', 4, 'log2'],
+              'n_estimators': [10, 50, 120],
+              'max_depth': [40, 20, 10],
+              'max_leaf_nodes': [5, 10, 2]}
 
 grid, grid_param, grid_score = grid_search(X_train, y_train, rfc, param_grid, cv=3)
 
 
 # Write your solution here :
-
+def fit(X_test,y_test):
+    y_pred=grid.predict(X_test)
+    variable1=confusion_matrix(y_test,y_pred)
+    variable2=classification_report(y_test,y_pred)
+    variable3=accuracy_score(y_test,y_pred)
+    return variable1,variable2,variable3
 
 
diff --git a/q02_fit/tests/__pycache__/__init__.cpython-36.pyc b/q02_fit/tests/__pycache__/__init__.cpython-36.pyc
index 5b1da020783fa9a059116ba98f7a4fdc73c700b1..a604d885a383c94cc21950df3e09cfe2284db39b 100644
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delta 49
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delta 38
tcmZ3$IF*szn3tDpak2bFb_-!A{fzwFRQ;0F;u3wA)Z*-t{DO(G&H&7g3-JH|

diff --git a/q02_fit/tests/__pycache__/test_q02_fit.cpython-36.pyc b/q02_fit/tests/__pycache__/test_q02_fit.cpython-36.pyc
index 3d6485624ed394e15bb321e45e5945ebb835250c..80d34ecf1d41da96300f078429de82dc5ca0fea0 100644
GIT binary patch
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delta 661
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