renamed and small changes

Topological_Machine_Learning/.ipynb_checkpoints/Untitled1-checkpoint.ipynb

-{
- "cells": [],
- "metadata": {},
- "nbformat": 4,
- "nbformat_minor": 2
-}

Topological_Machine_Learning/.ipynb_checkpoints/__init__.py-checkpoint.ipynb

-{
- "cells": [],
- "metadata": {},
- "nbformat": 4,
- "nbformat_minor": 2
-}

Topological_Machine_Learning/TDA_Prediction.py

-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
-
-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)
-    
-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
-
-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
\ No newline at end of file

Topological_Machine_Learning/__init__.py

-{
- "cells": [],
- "metadata": {},
- "nbformat": 4,
- "nbformat_minor": 2
-}

Topological_Machine_Learning/__init__.py.ipynb

-{
- "cells": [
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  }
- ],
- "metadata": {
-  "kernelspec": {
-   "display_name": "Python 3",
-   "language": "python",
-   "name": "python3"
-  },
-  "language_info": {
-   "codemirror_mode": {
-    "name": "ipython",
-    "version": 3
-   },
-   "file_extension": ".py",
-   "mimetype": "text/x-python",
-   "name": "python",
-   "nbconvert_exporter": "python",
-   "pygments_lexer": "ipython3",
-   "version": "3.7.3"
-  }
- },
- "nbformat": 4,
- "nbformat_minor": 2
-}