From 4f7870bc4c69492c912d0d945a5042d2cf9b6130 Mon Sep 17 00:00:00 2001
From: Abhimanyu22 <link2manyu@hotmail.com>
Date: Sat, 3 Nov 2018 15:00:04 +0000
Subject: [PATCH 1/5] Done

---
 __pycache__/__init__.cpython-36.pyc            | Bin 154 -> 153 bytes
 .../__pycache__/__init__.cpython-36.pyc        | Bin 178 -> 167 bytes
 q01_plot_corr/__pycache__/build.cpython-36.pyc | Bin 558 -> 740 bytes
 q01_plot_corr/build.py                         |  10 +++++++---
 .../tests/__pycache__/__init__.cpython-36.pyc  | Bin 167 -> 173 bytes
 .../test_q01_plot_corr.cpython-36.pyc          | Bin 791 -> 1102 bytes
 6 files changed, 7 insertions(+), 3 deletions(-)

diff --git a/__pycache__/__init__.cpython-36.pyc b/__pycache__/__init__.cpython-36.pyc
index abc397ac59f40d351e1861264050586541adce96..2e0dda939702cae2b73e2ccb1be7ca0ea27ffea5 100644
GIT binary patch
delta 80
zcmbQmIFpgXn3tDp#rC_=6FJOn-1IZ@b5r#llQJ@M6Z0xdjg0ie^NX^J3lfu4^^@~c
iQuWhP6H7{qQsawLb5fH_GV}A|3ySiyfK2^~HF5x3dL17C

delta 81
zcmbQqIE#_Pn3tC;r0Y!NL=JOXcW0}Z(Bjmh;+VvwjLhPU)a)3S)Z*-t{DPSDqSVU7
elKkA5f};Ga)Z`Kv9bb}~Tac4jk{UCyS`Gk$V;)lg

diff --git a/q01_plot_corr/__pycache__/__init__.cpython-36.pyc b/q01_plot_corr/__pycache__/__init__.cpython-36.pyc
index 460f88abffae2c2371906282e6e7f121c82a6603..06030891b06d348ffe5c5b6b27fa5df5a0d984bd 100644
GIT binary patch
delta 121
zcmdnQxSWy0n3tDp#rC_=6FJN?Li988b5r#llQJ@M6Z0xdjg0ie^NX^J3lfu4^^@~c
zQuWhP6H7{qQsawLb5fH_GV}A|3ySiyfK2^D1H<@&ocxmb<ou!{{rLFIyv&mLc)fzk
WTO2mI`6;D2sdkJE3=G9U%m4sodnzRW

delta 105
zcmZ3^xQUU&n3tC;r0Y!NL=N-NcxS7a(Bjmh;+VvwjLhPU)a)3S)Z*-t{DPSDqSVU7
zlKkA5f};Ga)Z`Kv9bb}~Tac4jk{VNJU>IMNnwS!wTwE5Pl30=$Uy>i6k`^<uQw{*>
C=O^y~

diff --git a/q01_plot_corr/__pycache__/build.cpython-36.pyc b/q01_plot_corr/__pycache__/build.cpython-36.pyc
index f4059a396f2f2d496c99f95048654e2c7471d9b9..84e0d8a6e36fba9bc4805b394a879f0940b5a6cc 100644
GIT binary patch
literal 740
zcmZ8f&5qMB5VjrXr(L>;Um=d%dfC8oMF_+dEdmaRfD~NYZIe1b*v{^D)t<t2AA~31
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literal 558
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diff --git a/q01_plot_corr/build.py b/q01_plot_corr/build.py
index edc724a..4c205d3 100644
--- a/q01_plot_corr/build.py
+++ b/q01_plot_corr/build.py
@@ -1,5 +1,5 @@
-# Default imports
 import pandas as pd
+import matplotlib.pyplot as plt
 from matplotlib.pyplot import yticks, xticks, subplots, set_cmap
 plt.switch_backend('agg')
 data = pd.read_csv('data/house_prices_multivariate.csv')
@@ -9,8 +9,12 @@
 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
+    
+    return
+
+
+
diff --git a/q01_plot_corr/tests/__pycache__/__init__.cpython-36.pyc b/q01_plot_corr/tests/__pycache__/__init__.cpython-36.pyc
index c4bc30d7704db1af3a7d76f564945a76f376cb2d..63d745fc25e5be6cbdffdce8217839362feeea44 100644
GIT binary patch
delta 100
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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..6b1ca9f94032f3486150fd069737fbe39bdbeabb 100644
GIT binary patch
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From 970cf40f65b0571c1e4c542243c14d4e2b420e72 Mon Sep 17 00:00:00 2001
From: Abhimanyu22 <link2manyu@hotmail.com>
Date: Sun, 4 Nov 2018 08:38:12 +0000
Subject: [PATCH 2/5] Done

---
 .../__pycache__/__init__.cpython-36.pyc       | Bin 167 -> 173 bytes
 .../__pycache__/build.cpython-36.pyc          | Bin 951 -> 938 bytes
 q02_best_k_features/build.py                  |  34 +++++++++++++++---
 .../tests/__pycache__/__init__.cpython-36.pyc | Bin 173 -> 179 bytes
 ...t_q02_percentile_k_features.cpython-36.pyc | Bin 0 -> 1966 bytes
 5 files changed, 30 insertions(+), 4 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..5846346716600f9f1b66e74c5c5ca17dd8a9837e 100644
GIT binary patch
delta 100
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xQuWhP6H7{qQsawLb5fH_GV}A|3ySiyfK2^D1Ect))Z&u(?0Bf6V*QDoasUYfB@6%n

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..224a23dbfd146f4e97f3cfc17b5ffa2be3e7bbd7 100644
GIT binary patch
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diff --git a/q02_best_k_features/build.py b/q02_best_k_features/build.py
index 9b1046a..a355137 100644
--- a/q02_best_k_features/build.py
+++ b/q02_best_k_features/build.py
@@ -1,12 +1,38 @@
+# %load q02_best_k_features/build.py
 # Default imports
-
 import pandas as pd
+import numpy as np
+from sklearn.feature_selection import SelectPercentile
+from sklearn.feature_selection import f_regression
 
 data = pd.read_csv('data/house_prices_multivariate.csv')
 
-from sklearn.feature_selection import SelectPercentile
-from sklearn.feature_selection import f_regression
+def percentile_k_features(data, k=20):
+    
+    X = data.iloc[:,:-1]
+    y = data['SalePrice']
+    f, _ = f_regression(X,y)
+    f = list(f)
+    xc = list(X.columns)
+    
+    f_sort = sorted(f)
+    xc_s = [x for _,x in sorted(zip(f, xc))]
+    req_len = int((k/100)*len(xc_s)) + 1
+ 
+    return xc_s[::-1][:req_len]
+
+    
+percentile_k_features(data)
+    
+    
+
+
+
+
+
+
+    
+
 
 
-# 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..1c1299456c0e0a19b05ab245e69c52f7ee500f46 100644
GIT binary patch
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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 1e25fbd0e5fc9f8dd41e35ba755e26d7313a4e48 Mon Sep 17 00:00:00 2001
From: Abhimanyu22 <link2manyu@hotmail.com>
Date: Fri, 16 Nov 2018 17:23:23 +0000
Subject: [PATCH 3/5] Done

---
 q03_rf_rfe/__pycache__/__init__.cpython-36.pyc | Bin 0 -> 164 bytes
 q03_rf_rfe/__pycache__/build.cpython-36.pyc    | Bin 0 -> 950 bytes
 q03_rf_rfe/build.py                            |  17 ++++++++++++++++-
 .../tests/__pycache__/__init__.cpython-36.pyc  | Bin 0 -> 170 bytes
 .../__pycache__/test_q03_rf_rfe.cpython-36.pyc | Bin 0 -> 1865 bytes
 5 files changed, 16 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
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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..11c82db 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 +7,20 @@
 from sklearn.feature_selection import RFE
 from sklearn.ensemble import RandomForestClassifier
 
+def rf_rfe(data):
+    
+    X,y = data.iloc[:,:-1], data.iloc[:,-1]
+    model = RandomForestClassifier()
+    rfe = RFE(model, int(data.shape[1]/2))
+    rfe.fit(X,y)
+    cols_list = rfe.get_support(indices=True)
+    cols_sort = [cols_list for _, cols_list in sorted(zip(rfe.ranking_[cols_list],cols_list))]
+    selected_cols = data.iloc[:,cols_sort]
+
+    return list(selected_cols.columns.values)
+
+rf_rfe(data)
+
+
 
-# 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 9ddf2a47e86395f1e35cd449a2221399637c3bfd Mon Sep 17 00:00:00 2001
From: Abhimanyu22 <link2manyu@hotmail.com>
Date: Fri, 16 Nov 2018 18:11:44 +0000
Subject: [PATCH 4/5] Done

---
 .../__pycache__/__init__.cpython-36.pyc       | Bin 0 -> 175 bytes
 .../__pycache__/build.cpython-36.pyc          | Bin 0 -> 836 bytes
 q04_select_from_model/build.py                |  19 +++++++++++++++++-
 .../tests/__pycache__/__init__.cpython-36.pyc | Bin 0 -> 181 bytes
 .../test_q04_select_from_model.cpython-36.pyc | Bin 0 -> 2085 bytes
 5 files changed, 18 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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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..9ede1f4 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 +7,21 @@
 
 data = pd.read_csv('data/house_prices_multivariate.csv')
 
+def select_from_model(data):
+    X,y = data.iloc[:,:-1], data.iloc[:,-1]
+    model = RandomForestClassifier(random_state=9)
+    model.fit(X,y)
+    rfe = SelectFromModel(model, prefit=True)
+    
+    rfe.transform(X)
+    cols_list = rfe.get_support(indices=True)
+    features_selected = data.iloc[:,cols_list]
+    
+    return list(features_selected.columns.values)
+
+select_from_model(data)
+    
+    
+
+
 
-# 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 7fa7285c361fb9499fab7e7c766bc54473314d5e Mon Sep 17 00:00:00 2001
From: Abhimanyu22 <link2manyu@hotmail.com>
Date: Fri, 16 Nov 2018 18:54:47 +0000
Subject: [PATCH 5/5] Done

---
 .../__pycache__/__init__.cpython-36.pyc       | Bin 0 -> 174 bytes
 .../__pycache__/build.cpython-36.pyc          | Bin 0 -> 1856 bytes
 q05_forward_selected/build.py                 |  50 +++++++++++++++++-
 .../tests/__pycache__/__init__.cpython-36.pyc | Bin 0 -> 180 bytes
 .../test_q05_forward_selected.cpython-36.pyc  | Bin 0 -> 2852 bytes
 5 files changed, 49 insertions(+), 1 deletion(-)
 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..ecb5408 100644
--- a/q05_forward_selected/build.py
+++ b/q05_forward_selected/build.py
@@ -1,3 +1,4 @@
+# %load q05_forward_selected/build.py
 # Default imports
 import pandas as pd
 from sklearn.linear_model import LinearRegression
@@ -6,5 +7,52 @@
 
 model = LinearRegression()
 
+def forward_selected(data, model):
+    df = data
+    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
+
+forward_selected(data, model)
+
+
 
-# 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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