From b57e996d01c9517d7c5dd429d9a7373bc6a87cd7 Mon Sep 17 00:00:00 2001
From: sannidh <soniknitr@gmail.com>
Date: Wed, 7 Nov 2018 01:35:15 +0000
Subject: [PATCH 1/5] Done

---
 __pycache__/__init__.cpython-36.pyc            | Bin 154 -> 149 bytes
 .../__pycache__/__init__.cpython-36.pyc        | Bin 178 -> 163 bytes
 q01_plot_corr/__pycache__/build.cpython-36.pyc | Bin 558 -> 736 bytes
 q01_plot_corr/build.py                         |   8 ++++++--
 .../tests/__pycache__/__init__.cpython-36.pyc  | Bin 167 -> 169 bytes
 .../test_q01_plot_corr.cpython-36.pyc          | Bin 791 -> 1098 bytes
 6 files changed, 6 insertions(+), 2 deletions(-)

diff --git a/__pycache__/__init__.cpython-36.pyc b/__pycache__/__init__.cpython-36.pyc
index abc397ac59f40d351e1861264050586541adce96..699a22ddb9727d2422b2ddfa151ff302c4cd7ca5 100644
GIT binary patch
delta 76
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delta 81
zcmbQrIE#_Pn3tC;r0Y!NL=JOXcW0}Z(Bjmh;+VvwjLhPU)a)3S)Z*-t{DPSDqSVU7
elKkA5f};Ga)Z`Kv9bb}~Tac4jk{UCyTn+$%7amIh

diff --git a/q01_plot_corr/__pycache__/__init__.cpython-36.pyc b/q01_plot_corr/__pycache__/__init__.cpython-36.pyc
index 460f88abffae2c2371906282e6e7f121c82a6603..8f1fb6cb0f15f22787853ef793306c73a6fc92c3 100644
GIT binary patch
delta 117
zcmdnQxR{Z{n3tE!)$vjEL=N+m0R4>o+*JMI#Js%Blnnjw{G#mQg2d!h{p9?VRQ<Hn
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delta 132
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diff --git a/q01_plot_corr/__pycache__/build.cpython-36.pyc b/q01_plot_corr/__pycache__/build.cpython-36.pyc
index f4059a396f2f2d496c99f95048654e2c7471d9b9..e3a1fc454abbe77a93ea9d2396cec511ddf0fe67 100644
GIT binary patch
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diff --git a/q01_plot_corr/build.py b/q01_plot_corr/build.py
index edc724a..37c509e 100644
--- a/q01_plot_corr/build.py
+++ b/q01_plot_corr/build.py
@@ -1,16 +1,20 @@
+# %load q01_plot_corr/build.py
 # Default imports
 import pandas as pd
 from matplotlib.pyplot import yticks, xticks, subplots, set_cmap
+import matplotlib.pyplot as plt
 plt.switch_backend('agg')
 data = pd.read_csv('data/house_prices_multivariate.csv')
 
-
 # Write your solution here:
 def plot_corr(data, size=11):
     corr = data.corr()
     fig, ax = subplots(figsize=(size, size))
-    set_cmap("YlOrRd")
+    set_cmap('YlOrRd')
     ax.matshow(corr)
     xticks(range(len(corr.columns)), corr.columns, rotation=90)
     yticks(range(len(corr.columns)), corr.columns)
     return ax
+
+
+
diff --git a/q01_plot_corr/tests/__pycache__/__init__.cpython-36.pyc b/q01_plot_corr/tests/__pycache__/__init__.cpython-36.pyc
index c4bc30d7704db1af3a7d76f564945a76f376cb2d..8f1b325fbab83e93cd05d3edb67d0b8a2b1b1f9c 100644
GIT binary patch
delta 96
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delta 94
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diff --git a/q01_plot_corr/tests/__pycache__/test_q01_plot_corr.cpython-36.pyc b/q01_plot_corr/tests/__pycache__/test_q01_plot_corr.cpython-36.pyc
index 40d2b706881e3ab76930c2164e7d4894f4b4633f..e7aaa527a712e452a7413fac8ca794876bb906cc 100644
GIT binary patch
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From 296a2d0b832dd8e88a8e45ed10df4429867451b2 Mon Sep 17 00:00:00 2001
From: sannidh <soniknitr@gmail.com>
Date: Wed, 7 Nov 2018 04:23:50 +0000
Subject: [PATCH 2/5] Done

---
 .../__pycache__/__init__.cpython-36.pyc         | Bin 167 -> 169 bytes
 .../__pycache__/build.cpython-36.pyc            | Bin 951 -> 984 bytes
 q02_best_k_features/build.py                    |  14 +++++++++++---
 .../tests/__pycache__/__init__.cpython-36.pyc   | Bin 173 -> 175 bytes
 ...est_q02_percentile_k_features.cpython-36.pyc | Bin 0 -> 1962 bytes
 5 files changed, 11 insertions(+), 3 deletions(-)
 create mode 100644 q02_best_k_features/tests/__pycache__/test_q02_percentile_k_features.cpython-36.pyc

diff --git a/q02_best_k_features/__pycache__/__init__.cpython-36.pyc b/q02_best_k_features/__pycache__/__init__.cpython-36.pyc
index 43047f0b7d121cffd870478bfcf87b31503ee2f1..1c511928767a5fa2790b902e0889865b1fdb02bd 100644
GIT binary patch
delta 96
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delta 94
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diff --git a/q02_best_k_features/__pycache__/build.cpython-36.pyc b/q02_best_k_features/__pycache__/build.cpython-36.pyc
index 8372777e40963b4c282006fe1233b5dbaa51cf8a..3fa9c113112c4ee8469a962dde4d22ed210d24bc 100644
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diff --git a/q02_best_k_features/build.py b/q02_best_k_features/build.py
index 9b1046a..f2ab766 100644
--- a/q02_best_k_features/build.py
+++ b/q02_best_k_features/build.py
@@ -1,12 +1,20 @@
+# %load q02_best_k_features/build.py
 # Default imports
 
 import pandas as pd
 
 data = pd.read_csv('data/house_prices_multivariate.csv')
 
-from sklearn.feature_selection import SelectPercentile
-from sklearn.feature_selection import f_regression
+from sklearn.feature_selection import SelectPercentile, f_regression, SelectFromModel
+
+def percentile_k_features(df, k=20):
+    selector = SelectPercentile(f_regression, percentile=k)
+    X,y = df.iloc[:,:-1], df.iloc[:,-1]
+    selector.fit(X,y)
+    idx_selected = selector.get_support(indices=True)
+    idx_sorted = [idx_selected for _, idx_selected in sorted(zip(selector.scores_[idx_selected], idx_selected), reverse=True)]
+    features_train = df.iloc[:,idx_sorted]
+    return list(features_train.columns.values)
 
 
-# Write your solution here:
 
diff --git a/q02_best_k_features/tests/__pycache__/__init__.cpython-36.pyc b/q02_best_k_features/tests/__pycache__/__init__.cpython-36.pyc
index 86a25cff523fa394416e407b58545caf2749163a..68d5c1c01abf24270f89b13844461c495d3b3e44 100644
GIT binary patch
delta 102
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diff --git a/q02_best_k_features/tests/__pycache__/test_q02_percentile_k_features.cpython-36.pyc b/q02_best_k_features/tests/__pycache__/test_q02_percentile_k_features.cpython-36.pyc
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GIT binary patch
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From 1d476b812893f61e6c5043798f4fb1574ec9a10c Mon Sep 17 00:00:00 2001
From: sannidh <soniknitr@gmail.com>
Date: Wed, 7 Nov 2018 04:44:09 +0000
Subject: [PATCH 3/5] Done

---
 q03_rf_rfe/__pycache__/__init__.cpython-36.pyc   | Bin 0 -> 160 bytes
 q03_rf_rfe/__pycache__/build.cpython-36.pyc      | Bin 0 -> 945 bytes
 q03_rf_rfe/build.py                              |  14 +++++++++++++-
 .../tests/__pycache__/__init__.cpython-36.pyc    | Bin 0 -> 166 bytes
 .../__pycache__/test_q03_rf_rfe.cpython-36.pyc   | Bin 0 -> 1861 bytes
 5 files changed, 13 insertions(+), 1 deletion(-)
 create mode 100644 q03_rf_rfe/__pycache__/__init__.cpython-36.pyc
 create mode 100644 q03_rf_rfe/__pycache__/build.cpython-36.pyc
 create mode 100644 q03_rf_rfe/tests/__pycache__/__init__.cpython-36.pyc
 create mode 100644 q03_rf_rfe/tests/__pycache__/test_q03_rf_rfe.cpython-36.pyc

diff --git a/q03_rf_rfe/__pycache__/__init__.cpython-36.pyc b/q03_rf_rfe/__pycache__/__init__.cpython-36.pyc
new file mode 100644
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diff --git a/q03_rf_rfe/__pycache__/build.cpython-36.pyc b/q03_rf_rfe/__pycache__/build.cpython-36.pyc
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diff --git a/q03_rf_rfe/build.py b/q03_rf_rfe/build.py
index e8a8d20..8086cb0 100644
--- a/q03_rf_rfe/build.py
+++ b/q03_rf_rfe/build.py
@@ -1,3 +1,4 @@
+# %load q03_rf_rfe/build.py
 # Default imports
 import pandas as pd
 
@@ -6,6 +7,17 @@
 from sklearn.feature_selection import RFE
 from sklearn.ensemble import RandomForestClassifier
 
+def rf_rfe(df):
+    model = RandomForestClassifier()
+    X,y = df.iloc[:,:-1], df.iloc[:,-1]
+    selector = RFE(model, int(df.shape[1]/2))
+    selector.fit(X,y)
+    idx_selected = selector.get_support(indices=True)
+    idx_sorted = [idx_selected for _, idx_selected in sorted(zip(selector.ranking_[idx_selected],idx_selected))]
+    features_train = df.iloc[:,idx_sorted]
+    return list(features_train.columns.values)
+
+
+
 
-# Your solution code here
 
diff --git a/q03_rf_rfe/tests/__pycache__/__init__.cpython-36.pyc b/q03_rf_rfe/tests/__pycache__/__init__.cpython-36.pyc
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From 9d12bd16b05f512a86cd89c498c949d1ac0afb02 Mon Sep 17 00:00:00 2001
From: sannidh <soniknitr@gmail.com>
Date: Wed, 7 Nov 2018 05:35:15 +0000
Subject: [PATCH 4/5] Done

---
 .../__pycache__/__init__.cpython-36.pyc          | Bin 0 -> 171 bytes
 .../__pycache__/build.cpython-36.pyc             | Bin 0 -> 824 bytes
 q04_select_from_model/build.py                   |  15 ++++++++++++++-
 .../tests/__pycache__/__init__.cpython-36.pyc    | Bin 0 -> 177 bytes
 .../test_q04_select_from_model.cpython-36.pyc    | Bin 0 -> 2081 bytes
 5 files changed, 14 insertions(+), 1 deletion(-)
 create mode 100644 q04_select_from_model/__pycache__/__init__.cpython-36.pyc
 create mode 100644 q04_select_from_model/__pycache__/build.cpython-36.pyc
 create mode 100644 q04_select_from_model/tests/__pycache__/__init__.cpython-36.pyc
 create mode 100644 q04_select_from_model/tests/__pycache__/test_q04_select_from_model.cpython-36.pyc

diff --git a/q04_select_from_model/__pycache__/__init__.cpython-36.pyc b/q04_select_from_model/__pycache__/__init__.cpython-36.pyc
new file mode 100644
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GIT binary patch
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diff --git a/q04_select_from_model/__pycache__/build.cpython-36.pyc b/q04_select_from_model/__pycache__/build.cpython-36.pyc
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diff --git a/q04_select_from_model/build.py b/q04_select_from_model/build.py
index 12dd1df..9a9e736 100644
--- a/q04_select_from_model/build.py
+++ b/q04_select_from_model/build.py
@@ -1,3 +1,4 @@
+# %load q04_select_from_model/build.py
 # Default imports
 from sklearn.feature_selection import SelectFromModel
 from sklearn.ensemble import RandomForestClassifier
@@ -6,5 +7,17 @@
 
 data = pd.read_csv('data/house_prices_multivariate.csv')
 
+def select_from_model(df):
+    X,y = df.iloc[:,:-1], df.iloc[:,-1]
+    clf = RandomForestClassifier(random_state=9)
+    clf.fit(X, y)
+    selector = SelectFromModel(clf, prefit=True)
+    selector.transform(X)
+    idx_selected = selector.get_support(indices=True)
+    features_train = df.iloc[:,idx_selected]
+    return list(features_train.columns.values)
+
+
+
+
 
-# Your solution code here
diff --git a/q04_select_from_model/tests/__pycache__/__init__.cpython-36.pyc b/q04_select_from_model/tests/__pycache__/__init__.cpython-36.pyc
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From d95a66c30a09baef760f46eca9869810f9ee3747 Mon Sep 17 00:00:00 2001
From: sannidh <soniknitr@gmail.com>
Date: Sun, 11 Nov 2018 13:43:40 +0000
Subject: [PATCH 5/5] Done

---
 .../__pycache__/__init__.cpython-36.pyc       | Bin 0 -> 170 bytes
 .../__pycache__/build.cpython-36.pyc          | Bin 0 -> 2043 bytes
 q05_forward_selected/build.py                 |  53 +++++++++++++++++-
 .../tests/__pycache__/__init__.cpython-36.pyc | Bin 0 -> 176 bytes
 .../test_q05_forward_selected.cpython-36.pyc  | Bin 0 -> 2848 bytes
 5 files changed, 51 insertions(+), 2 deletions(-)
 create mode 100644 q05_forward_selected/__pycache__/__init__.cpython-36.pyc
 create mode 100644 q05_forward_selected/__pycache__/build.cpython-36.pyc
 create mode 100644 q05_forward_selected/tests/__pycache__/__init__.cpython-36.pyc
 create mode 100644 q05_forward_selected/tests/__pycache__/test_q05_forward_selected.cpython-36.pyc

diff --git a/q05_forward_selected/__pycache__/__init__.cpython-36.pyc b/q05_forward_selected/__pycache__/__init__.cpython-36.pyc
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diff --git a/q05_forward_selected/build.py b/q05_forward_selected/build.py
index 8816abd..33e2e35 100644
--- a/q05_forward_selected/build.py
+++ b/q05_forward_selected/build.py
@@ -1,10 +1,59 @@
+# %load q05_forward_selected/build.py
 # Default imports
+from greyatomlib.feature_selection.q05_forward_selected.build import forward_selected
 import pandas as pd
+import numpy as np
+import math
 from sklearn.linear_model import LinearRegression
+from sklearn.metrics import mean_squared_error, r2_score
 
 data = pd.read_csv('data/house_prices_multivariate.csv')
 
-model = LinearRegression()
+def foward_selected(df, model=LinearRegression()):
+    X = df.drop(df.columns[len(df.columns)-1], axis=1)
+    y = df.iloc[:,-1]
+    col_list = X.columns
+    def select_cols(df, col_list):
+        return df[[item for item in col_list]]
+    Variable_f, Variable_f_max = [], []
+    Score_r2, Score_r2_max  = [], []
+    # the first feature
+    for index in range(len(col_list)):
+        feature_list=[col_list[index]]
+        new_X = select_cols(X,feature_list)
+        model.fit(new_X,y)
+        r2 = model.score(new_X,y)
+        Variable_f.append(new_X.columns[0])
+        Score_r2.append(r2)
+    max_r2_score = max(Score_r2)
+    Variable_f_max = [Variable_f[Score_r2.index(max_r2_score)]]
+    Score_r2_max.append(max_r2_score)
+    #The next features
+    new_Variable_f_max, new_Variable_f, new_Score_r2, new_Score_r2_max, new_Variable_f_max_capture, new_Score_r2_max_capture = [], [], [], [], [], []
+    new_Score_r2_max_capture.append(max_r2_score)
+    no_features_f_max = len(new_Variable_f)
+    new_Variable_f = Variable_f_max
+    def features(j):
+        feature_list=col_list[j]
+        return feature_list
+    for index in range(len(col_list)-1):
+        for k in range(len(col_list)-1):
+            if features(k) not in new_Variable_f:
+                new_Variable_f = Variable_f_max.copy()
+                new_Variable_f.append(features(k))
+                new_X1 = select_cols(X,new_Variable_f)
+                model.fit(new_X1,y)
+                new_r2 = model.score(new_X1,y)
+                new_Score_r2.append(new_r2)
+                new_max_r2_score = max(new_Score_r2)
+                new_Variable_f_max.append(new_X1.columns)
+                largest_indice = new_Score_r2.index(new_max_r2_score)
+                new_Variable_f_max_capture =list(new_Variable_f_max[largest_indice])        
+        new_Score_r2_max_capture.append(new_max_r2_score)
+        Variable_f_max = new_Variable_f_max_capture.copy()
+    return Variable_f_max, new_Score_r2_max_capture
+foward_selected(data, LinearRegression())
+
+
 
 
-# Your solution code here
diff --git a/q05_forward_selected/tests/__pycache__/__init__.cpython-36.pyc b/q05_forward_selected/tests/__pycache__/__init__.cpython-36.pyc
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