commit-live-students · SL345 · Jul 1, 2018 · Jul 3, 2018 · Jul 3, 2018 · Aug 14, 2018
diff --git a/__pycache__/__init__.cpython-36.pyc b/__pycache__/__init__.cpython-36.pyc
diff --git a/q01_load_data/__pycache__/__init__.cpython-36.pyc b/q01_load_data/__pycache__/__init__.cpython-36.pyc
diff --git a/q01_load_data/__pycache__/build.cpython-36.pyc b/q01_load_data/__pycache__/build.cpython-36.pyc
diff --git a/q01_load_data/build.py b/q01_load_data/build.py
@@ -1,4 +1,9 @@
+# %load q01_load_data/build.py
 import pandas as pd
 
 # Write your code below
-
+def load_data(path):
+    df = pd.read_csv(path, sep=';')
+    return df
+
+
diff --git a/q01_load_data/tests/__pycache__/__init__.cpython-36.pyc b/q01_load_data/tests/__pycache__/__init__.cpython-36.pyc
diff --git a/q01_load_data/tests/__pycache__/test.cpython-36.pyc b/q01_load_data/tests/__pycache__/test.cpython-36.pyc
diff --git a/q02_data_split/__pycache__/__init__.cpython-36.pyc b/q02_data_split/__pycache__/__init__.cpython-36.pyc
diff --git a/q02_data_split/__pycache__/build.cpython-36.pyc b/q02_data_split/__pycache__/build.cpython-36.pyc
diff --git a/q02_data_split/build.py b/q02_data_split/build.py
@@ -1,8 +1,16 @@
+# %load q02_data_split/build.py
 from greyatomlib.multivariate_regression_project.q01_load_data.build import load_data
 from sklearn.model_selection import train_test_split
 import pandas as pd
 df = load_data('data/student-mat.csv')
 
 # Write your code below
+def split_dataset(df):
+    X = df.iloc[:,:-1]
+    y = df.iloc[:,-1]
+    X_train,X_test,y_train,y_test = train_test_split(X,y,test_size=0.2)
+    data = (X_train,X_test,y_train,y_test)
+    return data
 
-
+
+
diff --git a/q02_data_split/tests/__pycache__/__init__.cpython-36.pyc b/q02_data_split/tests/__pycache__/__init__.cpython-36.pyc
diff --git a/q02_data_split/tests/__pycache__/test.cpython-36.pyc b/q02_data_split/tests/__pycache__/test.cpython-36.pyc
diff --git a/q03_data_encoding/__pycache__/__init__.cpython-36.pyc b/q03_data_encoding/__pycache__/__init__.cpython-36.pyc
diff --git a/q03_data_encoding/__pycache__/build.cpython-36.pyc b/q03_data_encoding/__pycache__/build.cpython-36.pyc
diff --git a/q03_data_encoding/build.py b/q03_data_encoding/build.py
@@ -1,3 +1,4 @@
+# %load q03_data_encoding/build.py
 from greyatomlib.multivariate_regression_project.q01_load_data.build import load_data
 from greyatomlib.multivariate_regression_project.q02_data_split.build import split_dataset
 from sklearn.preprocessing import LabelEncoder
@@ -8,7 +9,13 @@
 x_train, x_test, y_train, y_test =  split_dataset(df)
 
 # Write your code below
+def label_encode(x_train, x_test):
+    X_transform = x_train.apply(LabelEncoder().fit_transform)
+    X_test_transform = x_test.apply(LabelEncoder().fit_transform)
+    transformed_data = (X_transform,X_test_transform)
+    return transformed_data
 
-
+
+
 
 
diff --git a/q03_data_encoding/tests/__pycache__/__init__.cpython-36.pyc b/q03_data_encoding/tests/__pycache__/__init__.cpython-36.pyc
diff --git a/q03_data_encoding/tests/__pycache__/test.cpython-36.pyc b/q03_data_encoding/tests/__pycache__/test.cpython-36.pyc
diff --git a/q03_ohe_encoder/__pycache__/__init__.cpython-36.pyc b/q03_ohe_encoder/__pycache__/__init__.cpython-36.pyc
diff --git a/q03_ohe_encoder/__pycache__/build.cpython-36.pyc b/q03_ohe_encoder/__pycache__/build.cpython-36.pyc
diff --git a/q03_ohe_encoder/build.py b/q03_ohe_encoder/build.py
@@ -1,19 +1,27 @@
+# %load q03_ohe_encoder/build.py
 from greyatomlib.multivariate_regression_project.q01_load_data.build import load_data
 from greyatomlib.multivariate_regression_project.q02_data_split.build import split_dataset
 from sklearn.preprocessing import OneHotEncoder
-import pandas as pd
 import numpy as np
+import pandas as pd
+path = 'data/student-mat.csv'
+df = load_data(path)
+x_train, x_test, y_train, y_test = split_dataset(df)
+category_index1 = [x for x in range(len(df.columns)) if df[df.columns[x]].dtype == 'object']
 
-df = load_data('data/student-mat.csv')
-
-x_train, x_test, y_train, y_test =  split_dataset(df)
-
-category_index = [x for x in range(len(df.columns)) if df[df.columns[x]].dtype == 'object']
+def ohe_encode(x_train, x_test,category_index = category_index1):
+    cat_col_list = x_train.iloc[:,category_index]
 
+    for cat_col in cat_col_list:
+        # encoding in dummy variable
+        dummies = pd.get_dummies(x_train[cat_col], prefix=cat_col)
+        x_train = pd.concat([x_train, dummies], axis=1)
 
-# Write your code below
+        dummies1 = pd.get_dummies(x_test[cat_col], prefix=cat_col)
+        x_test = pd.concat([x_test, dummies1], axis=1)
 
-
+        # removing the  variable
+        x_train.drop(cat_col, axis=1, inplace=True)
+        x_test.drop(cat_col, axis=1, inplace=True)
+    return x_train,x_test
 
-
-
diff --git a/q03_ohe_encoder/tests/__pycache__/__init__.cpython-36.pyc b/q03_ohe_encoder/tests/__pycache__/__init__.cpython-36.pyc
diff --git a/q03_ohe_encoder/tests/__pycache__/test.cpython-36.pyc b/q03_ohe_encoder/tests/__pycache__/test.cpython-36.pyc
diff --git a/q05_linear_regression_model/__pycache__/__init__.cpython-36.pyc b/q05_linear_regression_model/__pycache__/__init__.cpython-36.pyc
diff --git a/q05_linear_regression_model/__pycache__/build.cpython-36.pyc b/q05_linear_regression_model/__pycache__/build.cpython-36.pyc
diff --git a/q05_linear_regression_model/build.py b/q05_linear_regression_model/build.py
@@ -1,3 +1,4 @@
+# %load q05_linear_regression_model/build.py
 from greyatomlib.multivariate_regression_project.q01_load_data.build import load_data
 from greyatomlib.multivariate_regression_project.q02_data_split.build import split_dataset
 
@@ -12,4 +13,9 @@
 
 
 # Write your code below
-
+def linear_regression(X_train,y_train):
+    lm = LinearRegression()
+    lm.fit(X_train,y_train)
+    return lm
+
+
diff --git a/q05_linear_regression_model/tests/__pycache__/__init__.cpython-36.pyc b/q05_linear_regression_model/tests/__pycache__/__init__.cpython-36.pyc
diff --git a/q05_linear_regression_model/tests/__pycache__/test.cpython-36.pyc b/q05_linear_regression_model/tests/__pycache__/test.cpython-36.pyc
diff --git a/q06_cross_validation/__pycache__/__init__.cpython-36.pyc b/q06_cross_validation/__pycache__/__init__.cpython-36.pyc
diff --git a/q06_cross_validation/__pycache__/build.cpython-36.pyc b/q06_cross_validation/__pycache__/build.cpython-36.pyc
diff --git a/q06_cross_validation/build.py b/q06_cross_validation/build.py
@@ -1,3 +1,4 @@
+# %load q06_cross_validation/build.py
 from greyatomlib.multivariate_regression_project.q01_load_data.build import load_data
 from greyatomlib.multivariate_regression_project.q02_data_split.build import split_dataset
 
@@ -18,4 +19,7 @@
 model =linear_regression(x_train,y_train)
 
 # Write your code below
-
+def cross_validation_regressor(model, x_train,y_train):
+    r2_score = cross_val_score(model,x_train,y_train,scoring='r2')
+    return np.mean(r2_score)
+
diff --git a/q06_cross_validation/tests/__pycache__/__init__.cpython-36.pyc b/q06_cross_validation/tests/__pycache__/__init__.cpython-36.pyc
diff --git a/q06_cross_validation/tests/__pycache__/test.cpython-36.pyc b/q06_cross_validation/tests/__pycache__/test.cpython-36.pyc
diff --git a/q07_regression_pred/__pycache__/__init__.cpython-36.pyc b/q07_regression_pred/__pycache__/__init__.cpython-36.pyc
diff --git a/q07_regression_pred/__pycache__/build.cpython-36.pyc b/q07_regression_pred/__pycache__/build.cpython-36.pyc
diff --git a/q07_regression_pred/build.py b/q07_regression_pred/build.py
@@ -1,3 +1,4 @@
+# %load q07_regression_pred/build.py
 
 from sklearn.metrics import mean_squared_error, mean_absolute_error, r2_score
 
@@ -20,3 +21,10 @@
 
 
 # Write your code below    
+def regression_predictor(model, x_test, y_test):
+    y_pred = model.predict(x_test)
+    mse =  mean_squared_error(y_test,y_pred)
+    mae = mean_absolute_error(y_test,y_pred)
+    r2 = r2_score(y_test,y_pred)
+    return y_pred , mse, mae, r2
+
diff --git a/q07_regression_pred/tests/__pycache__/__init__.cpython-36.pyc b/q07_regression_pred/tests/__pycache__/__init__.cpython-36.pyc
diff --git a/q07_regression_pred/tests/__pycache__/test.cpython-36.pyc b/q07_regression_pred/tests/__pycache__/test.cpython-36.pyc
diff --git a/q08_linear_model/__pycache__/__init__.cpython-36.pyc b/q08_linear_model/__pycache__/__init__.cpython-36.pyc
diff --git a/q08_linear_model/__pycache__/build.cpython-36.pyc b/q08_linear_model/__pycache__/build.cpython-36.pyc
diff --git a/q08_linear_model/build.py b/q08_linear_model/build.py
@@ -1,3 +1,4 @@
+# %load q08_linear_model/build.py
 import pandas as pd
 import numpy as np
 from greyatomlib.multivariate_regression_project.q01_load_data.build import load_data
@@ -16,5 +17,12 @@
 y_pred, mse, mae, r2 = regression_predictor(model, x_test, y_test)
 
 # Write your code below
+def linear_model(x_train, x_test, y_train, y_test):
+    model =linear_regression(x_train,y_train)
+    val = cross_validation_regressor(model,x_train,y_train)
+    y_pred, mse, mae, r2 = regression_predictor(model, x_test, y_test) 
+    d = {'cross_validation':[val],'rmse':[mse],'mae':[mae],'rsquared':[r2]}
+    stats = pd.DataFrame(data=d)
+    return model,y_pred,stats
 
-    
+
diff --git a/q08_linear_model/tests/__pycache__/__init__.cpython-36.pyc b/q08_linear_model/tests/__pycache__/__init__.cpython-36.pyc
diff --git a/q08_linear_model/tests/__pycache__/test.cpython-36.pyc b/q08_linear_model/tests/__pycache__/test.cpython-36.pyc
diff --git a/q09_advanced_model_q01_lasso/__pycache__/__init__.cpython-36.pyc b/q09_advanced_model_q01_lasso/__pycache__/__init__.cpython-36.pyc
diff --git a/q09_advanced_model_q01_lasso/__pycache__/build.cpython-36.pyc b/q09_advanced_model_q01_lasso/__pycache__/build.cpython-36.pyc
diff --git a/q09_advanced_model_q01_lasso/build.py b/q09_advanced_model_q01_lasso/build.py
@@ -1,3 +1,4 @@
+# %load q09_advanced_model_q01_lasso/build.py
 from greyatomlib.multivariate_regression_project.q01_load_data.build import load_data
 
 from greyatomlib.multivariate_regression_project.q02_data_split.build import split_dataset
@@ -19,5 +20,14 @@
 x_train,x_test = label_encode(x_train,x_test)
 
 # Write your solution here
+def lasso(x_train, x_test, y_train, y_test, alpha=0.1):
+    np.random.seed(9)
+    model =Lasso(alpha=alpha)
+    model.fit(x_train,y_train)
+    val = cross_validation_regressor(model,x_train,y_train)
+    y_pred, mse, mae, r2 = regression_predictor(model, x_test, y_test) 
+    rmse =(mse ** 0.5)
+    d = {'cross_validation':[val],'rmse':[rmse],'mae':[mae],'r2':[r2]}
+    stats = pd.DataFrame(data=d)
+    return model,y_pred,stats
 
-
diff --git a/q09_advanced_model_q01_lasso/tests/__pycache__/__init__.cpython-36.pyc b/q09_advanced_model_q01_lasso/tests/__pycache__/__init__.cpython-36.pyc
diff --git a/q09_advanced_model_q01_lasso/tests/__pycache__/test.cpython-36.pyc b/q09_advanced_model_q01_lasso/tests/__pycache__/test.cpython-36.pyc
diff --git a/q09_advanced_model_q02_ridge/__pycache__/__init__.cpython-36.pyc b/q09_advanced_model_q02_ridge/__pycache__/__init__.cpython-36.pyc
diff --git a/q09_advanced_model_q02_ridge/__pycache__/build.cpython-36.pyc b/q09_advanced_model_q02_ridge/__pycache__/build.cpython-36.pyc
diff --git a/q09_advanced_model_q02_ridge/build.py b/q09_advanced_model_q02_ridge/build.py
@@ -1,3 +1,4 @@
+# %load q09_advanced_model_q01_lasso/build.py
 from greyatomlib.multivariate_regression_project.q01_load_data.build import load_data
 
 from greyatomlib.multivariate_regression_project.q02_data_split.build import split_dataset
@@ -8,18 +9,28 @@
 from sklearn.linear_model import Ridge
 import numpy as np
 import pandas as pd
+from sklearn.metrics import mean_squared_error, mean_absolute_error, r2_score
 
 from greyatomlib.multivariate_regression_project.q06_cross_validation.build import cross_validation_regressor
 np.random.seed(9)
 
 df = load_data('data/student-mat.csv')
- 
+
 x_train, x_test, y_train, y_test =  split_dataset(df)
 
 x_train,x_test = label_encode(x_train,x_test)
 
-# Write your code below
-
-
-
+# Write your solution here
+def ridge(x_train, x_test, y_train, y_test, alpha=0.1):
+    np.random.seed(9)
+    model =Ridge(alpha=alpha,normalize=True)
+    model.fit(x_train,y_train)
+    val = cross_validation_regressor(model,x_train,y_train)
+    y_pred = model.predict(x_test)
+    mse= np.sqrt(mean_squared_error(y_test, y_pred))
+    mae= mean_absolute_error (y_test,y_pred)
+    r2= r2_score(y_test,y_pred)    
+    d = {'cross_validation':[val],'rmse':[mse],'mae':[mae],'r2':[r2]}
+    stats = pd.DataFrame(data=d)
+    return model,y_pred,stats
 
diff --git a/q09_advanced_model_q02_ridge/tests/__pycache__/__init__.cpython-36.pyc b/q09_advanced_model_q02_ridge/tests/__pycache__/__init__.cpython-36.pyc
diff --git a/q09_advanced_model_q02_ridge/tests/__pycache__/test.cpython-36.pyc b/q09_advanced_model_q02_ridge/tests/__pycache__/test.cpython-36.pyc
diff --git a/q10_data_missing_values/__pycache__/__init__.cpython-36.pyc b/q10_data_missing_values/__pycache__/__init__.cpython-36.pyc
diff --git a/q10_data_missing_values/__pycache__/build.cpython-36.pyc b/q10_data_missing_values/__pycache__/build.cpython-36.pyc
diff --git a/q10_data_missing_values/build.py b/q10_data_missing_values/build.py
@@ -1,3 +1,4 @@
+# %load q10_data_missing_values/build.py
 from greyatomlib.multivariate_regression_project.q01_load_data.build import load_data
 from greyatomlib.multivariate_regression_project.q02_data_split.build import split_dataset
 from greyatomlib.multivariate_regression_project.q03_data_encoding.build import label_encode
@@ -10,4 +11,8 @@
 x_train,x_test = label_encode(x_train,x_test)
 
 # Write your code below
-
+def describe_df(x_train):
+    describe = x_train.describe()
+    value_counts = x_train.apply(pd.value_counts)
+    return describe, value_counts
+
diff --git a/q10_data_missing_values/tests/__pycache__/__init__.cpython-36.pyc b/q10_data_missing_values/tests/__pycache__/__init__.cpython-36.pyc
diff --git a/q10_data_missing_values/tests/__pycache__/test.cpython-36.pyc b/q10_data_missing_values/tests/__pycache__/test.cpython-36.pyc
diff --git a/q11_feature_selection_q01_plot_corr/__pycache__/__init__.cpython-36.pyc b/q11_feature_selection_q01_plot_corr/__pycache__/__init__.cpython-36.pyc
diff --git a/q11_feature_selection_q01_plot_corr/__pycache__/build.cpython-36.pyc b/q11_feature_selection_q01_plot_corr/__pycache__/build.cpython-36.pyc
diff --git a/q11_feature_selection_q01_plot_corr/build.py b/q11_feature_selection_q01_plot_corr/build.py
@@ -1,14 +1,11 @@
+# %load q11_feature_selection_q01_plot_corr/build.py
 
 import matplotlib.pyplot as plt
 from matplotlib.pyplot import yticks, xticks, subplots, set_cmap
 from greyatomlib.multivariate_regression_project.q01_load_data.build import load_data
-
-
 from greyatomlib.multivariate_regression_project.q02_data_split.build import split_dataset
-
-
-
 from greyatomlib.multivariate_regression_project.q03_data_encoding.build import label_encode
+import seaborn as sns
 
 df = load_data('data/student-mat.csv')
 
@@ -21,6 +18,12 @@
 
 #Remember to concatenate training features and labels if you want to check that scatterplots which I would prefer.You are free to explore labels to labels, features to features ,etc scatterplots as you want by passing arguments
 #============================================================================
-#visualise_data(pd.concat([x_train,y_train],axis=1),"../images/data_image.png")
+#visualise_data(pd.concat([x_train,y_train],axis=1),'../images/data_image.png')
 
 # Write your solution here:
+def plot_corr(df,size=11):
+    fig,ax = plt.subplots(figsize=(size,size))
+    corr = df.corr()
+    sns.heatmap(corr,cmap='YlOrRd')
+    plt.show()
+
diff --git a/q11_feature_selection_q01_plot_corr/tests/__pycache__/__init__.cpython-36.pyc b/q11_feature_selection_q01_plot_corr/tests/__pycache__/__init__.cpython-36.pyc
diff --git a/q11_feature_selection_q01_plot_corr/tests/__pycache__/test.cpython-36.pyc b/q11_feature_selection_q01_plot_corr/tests/__pycache__/test.cpython-36.pyc
diff --git a/q11_feature_selection_q02_best_k_features/__pycache__/__init__.cpython-36.pyc b/q11_feature_selection_q02_best_k_features/__pycache__/__init__.cpython-36.pyc
diff --git a/q11_feature_selection_q02_best_k_features/__pycache__/build.cpython-36.pyc b/q11_feature_selection_q02_best_k_features/__pycache__/build.cpython-36.pyc
diff --git a/q11_feature_selection_q02_best_k_features/build.py b/q11_feature_selection_q02_best_k_features/build.py
@@ -1,3 +1,4 @@
+# %load q11_feature_selection_q02_best_k_features/build.py
 # Default imports
 from sklearn.feature_selection import SelectPercentile
 from sklearn.feature_selection import f_regression
@@ -20,8 +21,15 @@
 
 np.random.seed(9)
 # Write your code below
-
-
-
+def percentile_k_features(x_train, y_train, k=50):
+    selector = SelectPercentile(f_regression,percentile=k)
+    selector.fit_transform(x_train, y_train)
+    scores = selector.scores_[selector.get_support()]
+    features = x_train.columns.values[selector.get_support()]
+    features_scores_list = list(zip(features,scores))
+    df = pd.DataFrame(features_scores_list, columns=['Features','Scores'])
+    sorted_list = df.sort_values('Scores',ascending=False)
+    top_k_predictors = list(sorted_list['Features'])
+    return top_k_predictors
 
 
diff --git a/q11_feature_selection_q02_best_k_features/tests/__pycache__/__init__.cpython-36.pyc b/q11_feature_selection_q02_best_k_features/tests/__pycache__/__init__.cpython-36.pyc
diff --git a/q11_feature_selection_q02_best_k_features/tests/__pycache__/test.cpython-36.pyc b/q11_feature_selection_q02_best_k_features/tests/__pycache__/test.cpython-36.pyc
diff --git a/q12_feature_selection/__pycache__/__init__.cpython-36.pyc b/q12_feature_selection/__pycache__/__init__.cpython-36.pyc
diff --git a/q12_feature_selection/__pycache__/build.cpython-36.pyc b/q12_feature_selection/__pycache__/build.cpython-36.pyc
diff --git a/q12_feature_selection/build.py b/q12_feature_selection/build.py
@@ -1,18 +1,21 @@
-# import matplotlib.pyplot as plt
+# %load q12_feature_selection/build.py
+import matplotlib.pyplot as plt
 from greyatomlib.multivariate_regression_project.q01_load_data.build import load_data
 from greyatomlib.multivariate_regression_project.q02_data_split.build import split_dataset
-
 from greyatomlib.multivariate_regression_project.q03_data_encoding.build import label_encode
-
 from greyatomlib.multivariate_regression_project.q11_feature_selection_q02_best_k_features.build import percentile_k_features
-
 from greyatomlib.multivariate_regression_project.q11_feature_selection_q01_plot_corr.build import plot_corr
-
-
+import seaborn as sns
 import pandas as pd
+
 df = load_data('data/student-mat.csv')
 
 x_train, x_test, y_train, y_test =  split_dataset(df)
 x_train,x_test = label_encode(x_train,x_test)
 
 # Write your code below
+def feature_selection(x_train, y_train, k=50):
+    plot_corr(x_train)
+    reduced_features = percentile_k_features(x_train,y_train,k)
+    return reduced_features
+
diff --git a/q12_feature_selection/tests/__pycache__/__init__.cpython-36.pyc b/q12_feature_selection/tests/__pycache__/__init__.cpython-36.pyc
diff --git a/q12_feature_selection/tests/__pycache__/test.cpython-36.pyc b/q12_feature_selection/tests/__pycache__/test.cpython-36.pyc
diff --git a/q13_plot_residuals/__pycache__/__init__.cpython-36.pyc b/q13_plot_residuals/__pycache__/__init__.cpython-36.pyc
diff --git a/q13_plot_residuals/__pycache__/build.cpython-36.pyc b/q13_plot_residuals/__pycache__/build.cpython-36.pyc
diff --git a/q13_plot_residuals/build.py b/q13_plot_residuals/build.py
@@ -1,5 +1,16 @@
-
-
+# %load q13_plot_residuals/build.py
+import matplotlib
+matplotlib.use('Agg')
 import matplotlib.pyplot as plt
 
 # Write your code below
+def plot_residuals(y_test,y_pred,name):
+    residual = y_test - y_pred
+    plt.figure(figsize=(16,7))
+    plt.scatter(y_test, residuals)
+    plt.title('Residual plot')
+    plt.xlabel('Grade')
+    plt.ylabel('Residuals')
+    plt.show()
+
+
diff --git a/q13_plot_residuals/tests/__pycache__/__init__.cpython-36.pyc b/q13_plot_residuals/tests/__pycache__/__init__.cpython-36.pyc
diff --git a/q13_plot_residuals/tests/__pycache__/test.cpython-36.pyc b/q13_plot_residuals/tests/__pycache__/test.cpython-36.pyc
diff --git a/q14_benchmarking/__pycache__/__init__.cpython-36.pyc b/q14_benchmarking/__pycache__/__init__.cpython-36.pyc
diff --git a/q14_benchmarking/__pycache__/build.cpython-36.pyc b/q14_benchmarking/__pycache__/build.cpython-36.pyc
diff --git a/q14_benchmarking/build.py b/q14_benchmarking/build.py
@@ -1,15 +1,12 @@
+# %load q14_benchmarking/build.py
 from greyatomlib.multivariate_regression_project.q01_load_data.build import load_data
 from greyatomlib.multivariate_regression_project.q02_data_split.build import split_dataset
-
 from greyatomlib.multivariate_regression_project.q03_data_encoding.build import label_encode
 from greyatomlib.multivariate_regression_project.q05_linear_regression_model.build import linear_regression
 from greyatomlib.multivariate_regression_project.q06_cross_validation.build import cross_validation_regressor
 from greyatomlib.multivariate_regression_project.q07_regression_pred.build import regression_predictor
-
-
 from greyatomlib.multivariate_regression_project.q08_linear_model.build import linear_model
 from greyatomlib.multivariate_regression_project.q12_feature_selection.build import feature_selection
-
 from greyatomlib.multivariate_regression_project.q09_advanced_model_q01_lasso.build import lasso
 from greyatomlib.multivariate_regression_project.q09_advanced_model_q02_ridge.build import ridge
 
@@ -26,5 +23,15 @@
 
 
 # Write your code below
+def create_stats(x_train,x_test,y_train,y_test):
+    lasso_stats = lasso(x_train,x_test,y_train,y_test,alpha=0.1)[2]
+    lasso_f_ft = feature_selection(x_train,y_train,k=50)
+    lasso_stats_ft = lasso(x_train[lasso_f_ft],x_test[lasso_f_ft],y_train,y_test,alpha=0.1)[2]
+    ridge_stats = ridge(x_train,x_test,y_train,y_test,alpha=0.1)[2]
+    ridge_f_ft = feature_selection(x_train,y_train,k=50)
+    ridge_stats_ft = ridge(x_train[ridge_f_ft],x_test[ridge_f_ft],y_train,y_test,alpha=0.1)[2]
+    complete_stats = pd.concat([lasso_stats,lasso_stats_ft,ridge_stats,ridge_stats_ft],axis=1)
+    return complete_stats
+
 
 
diff --git a/q14_benchmarking/tests/__pycache__/__init__.cpython-36.pyc b/q14_benchmarking/tests/__pycache__/__init__.cpython-36.pyc
diff --git a/q14_benchmarking/tests/__pycache__/test.cpython-36.pyc b/q14_benchmarking/tests/__pycache__/test.cpython-36.pyc