### Improving the linear regression model using synthetic variables

December 3, 2019

Improving the linear regression model using synthetic variables Parking Birmingham occupancy analysis Source of data: https://archive.ics.uci.edu/ml/datasets/Parking+Birmingham In [1]: import pandas as pd df = pd.read_csv(‘c:/TF/ParkingBirmingham.csv’) df.head(3) […]

### Polynomial regression model

December 2, 2019

Polynomial regression model Polynomial regression model is technically a special case of multiple linear regression. This is definitions and explanation found in Wikipedia: https://en.wikipedia.org/wiki/Polynomial_regression. Just […]

### Tutorial: Linear Regression – Tensorflow, calculation of R Square (#4/281120191525)

November 28, 2019

We continue to learn how to build multiple linear regression models. This time we will build a model using the Tensorflow library. As before, the […]

### Tutorial: Linear Regression – Sklearn regression model (#3/281120191333)

November 28, 2019

In the previous part, we tried to build a model by trying to explain the level of carbon monoxide pollution based on temperature and pressure. […]

### Tutorial: Linear Regression – Time variables and shifts. Use of offset in variable correlation (#2/271120191334)

November 27, 2019

Part 2. Simple multifactorial linear regression In the previous part of this tutorial, we cleaned the data file from the measuring station. A new, completed […]

### Tutorial: Linear Regression – preliminary data preparation (#1/271120191024)

November 27, 2019

Part 1. Preliminary data preparation   AirQualityUCI Source of data: https://archive.ics.uci.edu/ml/datasets/Air+Quality In [1]: import pandas as pd df = pd.read_csv(‘c:/TS/AirQualityUCI.csv’, sep=’;’) df.head(3) Out[1]:   Date […]

### Example of the use of shift for linear regression in Python. How to find optimal correlation shift?

November 14, 2019

What is this the correlation shift? In supervised deep machine learning we have two directions: classification and regression. Regression needs continuous values of data. Because […]

### (Part 2) Process of forecasting the output electricity for power plant working in combined cycle by the linear regression equation

September 27, 2019

Correctly carried out linear regression model is the mapping of reality. It can be used to diagnostic systems, to prevent failures or even installation stoppage. […]

### (Part 1) Process of forecasting the output electricity for power plant working in combined cycle by the linear regression equation

September 27, 2019

Today we find out how to create simple regression model to predict level of output electricity in power plant works in combined cycle. Źródło bazy […]