From 48923a96cece18261efd2fba74a643c371de46af Mon Sep 17 00:00:00 2001
From: shawk masboob <masboob.shawk@gmail.com>
Date: Thu, 13 Feb 2020 23:40:51 -0500
Subject: [PATCH] adding PROJECT_Auto_Documentation
---
Models/0214-PROJECT_Auto_Documentation.py | 93 +++++++++++++++++++++++
1 file changed, 93 insertions(+)
create mode 100644 Models/0214-PROJECT_Auto_Documentation.py
diff --git a/Models/0214-PROJECT_Auto_Documentation.py b/Models/0214-PROJECT_Auto_Documentation.py
new file mode 100644
index 0000000..81bd176
--- /dev/null
+++ b/Models/0214-PROJECT_Auto_Documentation.py
@@ -0,0 +1,93 @@
+# importing toy & real world datasets from the scikit-learn library
+
+from sklearn import datasets
+
+def dataload():
+ """
+ upload toy datasets from scikit-learn
+ """
+ data = None
+ return data
+
+def datafetch(file_name):
+ """
+ upload real world datasets from scikit-learn
+ """
+ data = None
+ print("reading data from:", file_name)
+ return data
+
+# standard descriptive statistic analysis of data
+
+def descriptive_statistic(df):
+ """
+ Provides brief descriptive statistics on dataset.
+ Takes dataframe as input.
+ """
+ print("Type : ", None, "\n\n")
+ print("Shape : ", None)
+ print("Head -- \n", None)
+ print("\n\n Tail -- \n", None)
+ print("Describe : ", None)
+
+
+# model selection
+
+def model_selection(df):
+ """
+ Takes dateframe as input. Performs foward/backward stepwise
+ regression. Returns best model for both methods.
+ """
+ null_fit = None
+ foward_step = None
+ backward_step = None
+ return foward_step, backward_step
+
+# model accuracy
+
+def MSE_fit(fit):
+ """
+ Takes in a fitted model as the input.
+ Calculates the MSU of the fitted model.
+ Outputs the model's MSE.
+ """
+ MSE = None
+ return MSE
+
+def accuracy_metrics(fit, MSE):
+ """
+ This function is used for model validation. It returns a dictionary
+ of several regression model accuracy metrics. Its inputs are a fitted model
+ and the MSE of the fitted model.
+ """
+ d = dict()
+ sumObj = None
+ SSE = None
+ n = None
+ p = None
+ pr = None
+ d['R2'] = None
+ d['R2ad'] = None
+ d['AIC'] = None
+ d['BIC'] = None
+ d['PRESS'] = None
+ d['Cp']= None
+ return d
+
+# test code
+
+file_name = 'data.csv'
+
+a = datafetch(file_name)
+print(a)
+
+b = descriptive_statistic(a)
+print(b)
+
+c = model_selection(a)
+print(c)
+
+d = MSE_fit(c)
+print(d)
+
+print(accuracy_metrics(c, d))
\ No newline at end of file
--
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