From cca6b43a6f86fb082a00f49a99d43ba3f52df6aa Mon Sep 17 00:00:00 2001
From: PBPatil <theprasadpatil@gmail.com>
Date: Sun, 29 Apr 2018 18:44:19 +0000
Subject: [PATCH] Done

---
 __pycache__/__init__.cpython-36.pyc           | Bin 150 -> 145 bytes
 .../__pycache__/__init__.cpython-36.pyc       | Bin 166 -> 161 bytes
 .../__pycache__/build.cpython-36.pyc          | Bin 809 -> 1469 bytes
 q01_grid_search/build.py                      |  48 +++++++++++++++---
 .../tests/__pycache__/__init__.cpython-36.pyc | Bin 172 -> 167 bytes
 .../test_q01_grid_search.cpython-36.pyc       | Bin 4199 -> 4194 bytes
 q02_fit/__pycache__/__init__.cpython-36.pyc   | Bin 158 -> 153 bytes
 q02_fit/__pycache__/build.cpython-36.pyc      | Bin 1316 -> 1358 bytes
 q02_fit/build.py                              |  19 +++++--
 .../tests/__pycache__/__init__.cpython-36.pyc | Bin 164 -> 159 bytes
 .../__pycache__/test_q02_fit.cpython-36.pyc   | Bin 2960 -> 2651 bytes
 11 files changed, 57 insertions(+), 10 deletions(-)

diff --git a/__pycache__/__init__.cpython-36.pyc b/__pycache__/__init__.cpython-36.pyc
index 494c0e423d78629e57676c58ba01e9e4fe944241..0802d9357dc63b0d2ca2bb68b5c73a00dfbbd392 100644
GIT binary patch
delta 48
zcmbQnIFXUvn3tE!y7$UNb_-cM{fzwFRQ&*_fW(r_9R2Y8qU_>=#N<@{<ouM>iHW8F
DTx<`q

delta 53
zcmbQpIE|6rn3tF9PJH7;b_*qE{fzwFRQ>d#)XKz?{9JvP{N&Qy)Vz{n{eYtUtkmR^
I;)yY)0L8HqWB>pF

diff --git a/q01_grid_search/__pycache__/__init__.cpython-36.pyc b/q01_grid_search/__pycache__/__init__.cpython-36.pyc
index eed5319ad7e677d36d4aa0a041666797cfc18e79..395921122abc46e0e32252ab879bb7b707219930 100644
GIT binary patch
delta 48
zcmZ3+xR8<En3tE!y7$UNb_-cQ{fzwFRQ&*_fW(r_9R2Y8qU_>=#N<@{<ouM>iHWWN
DWLyvN

delta 53
zcmZ3;xQvnAn3tF9PJH7;b_=Co{fzwFRQ>d#)XKz?{9JvP{N&Qy)Vz{n{eYtUtkmR^
I;)yY?0M3yTqyPW_

diff --git a/q01_grid_search/__pycache__/build.cpython-36.pyc b/q01_grid_search/__pycache__/build.cpython-36.pyc
index cac4a0ba09e01d39b61ee5fb68a6a9cfed1ec303..6ba330c6902bb8b264f64671e041806f2c634cbe 100644
GIT binary patch
literal 1469
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delta 360
zcmYk2Jxc>Y5Qca5KC`*=BSMT;HX;Gx0=6O+{(zv3EJ`@Do0#J^CwrG7l|@KtAy<oa
z+6Z?3k!!`mKVV^_b0<P(n3s2+VPKfI`og|H@_qKTeCAJ-kaw~YHu_VnbcrH}fS7P1
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z?LkR=X-QA|!WA{a9?UC~ukm%h!8adY_nn4-3({`A>;ZuH`GcWbcw>7jUz!K`hk0{d
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diff --git a/q01_grid_search/build.py b/q01_grid_search/build.py
index 20c99a1..56ffb8e 100644
--- a/q01_grid_search/build.py
+++ b/q01_grid_search/build.py
@@ -1,8 +1,10 @@
+# %load q01_grid_search/build.py
 # Default imports
 
 import warnings
-warnings.filterwarnings("ignore")
+warnings.filterwarnings('ignore')
 import pandas as pd
+import numpy as np
 from sklearn.model_selection import train_test_split
 from sklearn.ensemble import RandomForestClassifier
 from sklearn.model_selection import GridSearchCV
@@ -12,11 +14,45 @@
 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]}
+
+rf = RandomForestClassifier(random_state=9, oob_score=True)
+def grid_search(X_train, y_train,rf, param_grid, cv=3):
+    model = GridSearchCV(estimator=rf, param_grid=param_grid, cv=cv)
+    model.fit(X_train, y_train)
+    var1 = list(model.cv_results_['params'])
+    var2 = np.array(model.cv_results_['mean_test_score'])
+    return model, var1, var2
+
+rf = RandomForestClassifier(random_state=9, oob_score=True)
+def grid_search(X_train, y_train,rf, param_grid, cv=3):
+    model = GridSearchCV(estimator=rf, param_grid=param_grid, cv=cv)
+    model.fit(X_train, y_train)
+    var1 = list(model.cv_results_['params'])
+    var2 = np.array(model.cv_results_['mean_test_score'])
+    return model, var1, var2
+    
+grid_search(X_train, y_train,rf, param_grid, cv=3)
+
+
+
+
+
+
+
+
+
+
+ 
+
+
+
+
+
+
 
 
-# Write your solution here :
 
diff --git a/q01_grid_search/tests/__pycache__/__init__.cpython-36.pyc b/q01_grid_search/tests/__pycache__/__init__.cpython-36.pyc
index 31ac32889b610935d2c1830c3823c926b02a7da2..209f34e003cf550ba97666610157ba79706e7a4b 100644
GIT binary patch
delta 48
zcmZ3(xSWyQn3tE!z4yvQb_>}M{fzwFRQ&*_fW(r_9R2Y8qU_>=#N<@{<ouM>iHY6-
DX(|vE

delta 53
zcmZ3^xQ3D4n3tF9hU2`6>=sIq`WgATsru<fsg;Q(`MLTo`N^fZsd**E`T<4xS*gh-
I#S>$^0nqIdw*UYD

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 bf1afbe383899abd6e94cfec577d467a76e04456..a0b18a19027217d2c7489231bad8985df2daf8dc 100644
GIT binary patch
delta 832
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delta 824
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int&V_#TF4?l3H8>PEt{9l@Ja%X@N9jm_1ofzytv7KABYj

diff --git a/q02_fit/__pycache__/__init__.cpython-36.pyc b/q02_fit/__pycache__/__init__.cpython-36.pyc
index 97c33cb307234e9b028e1705b5c23f75871114b0..2eb7f9c5b69c6fe7de349a710dc903da50030d30 100644
GIT binary patch
delta 48
zcmbQoIFpgxn3tE!y7$UNb_-cI{fzwFRQ&*_fW(r_9R2Y8qU_>=#N<@{<ouM>iHWuV
DU}O)`

delta 53
zcmbQqIFFItn3tF9PJH7;b_*qM{fzwFRQ>d#)XKz?{9JvP{N&Qy)Vz{n{eYtUtkmR^
I;)yY~0Lmc}ga7~l

diff --git a/q02_fit/__pycache__/build.cpython-36.pyc b/q02_fit/__pycache__/build.cpython-36.pyc
index 3d41a6281f0afb822a77a1045ed697c10ee3c678..b8fb17232bde4e5e9839a1e9c5d2523db3d7e0ec 100644
GIT binary patch
delta 575
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delta 513
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diff --git a/q02_fit/build.py b/q02_fit/build.py
index fbafb1a..64f8f15 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
@@ -13,15 +14,25 @@
 
 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
+def fit(X_test,y_test):
+    pass
+X_test.shape
+type(y_test)
 
 
diff --git a/q02_fit/tests/__pycache__/__init__.cpython-36.pyc b/q02_fit/tests/__pycache__/__init__.cpython-36.pyc
index 4a01850f21d216d8ccbec7c32d5325e707bae019..563c9dd9fff4f65b92569b6884750195aef8bfc4 100644
GIT binary patch
delta 48
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delta 53
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index 413b2fcb0350f27eb149eb2d1be1830ba8545d0c..850116c32d74a7e8893619315ca841511a7453c9 100644
GIT binary patch
delta 554
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delta 746
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