Читать книгу Data Mining and Machine Learning Applications - Группа авторов - Страница 23

We will discuss Python for data mining in this last section with various techniques. Regression is a technique to reduce errors by estimating the relationship that may exist between variables. It is also possible to form clusters in Python. One can implement this regression method using Python as follows:

User can develop a regression model for given variables and helps researchers, students to estimate the relationship exists between them. It also helps in classifying the given objects, analyze the clusters formed, etc., using tools provided in Python [24].

 Panda,” a library supported by Python, helps to clean and process the input data.

 NumPy—a package supported by Python to perform computations.

 Matplotlib—once the data is processed, there is a need to visualize this data, and it is possible using this package supported by Python.

 Scikit-learn—a library supported by Python to model the data.

Python used in data mining, and machine learning executes the following steps:

1 Import the required libraries

2 Dataset loading (import)

3 If the dataset consists of missing data, then it must handle this missing data

4 Classifying or handling categorical data

5 Dividing the dataset into training and testing dataset

6 Features scaling (actually, it is a transformation of variables).

Installation and Setup of Python

 1) Click on the link below and select OS: https://www.anaconda.com/download/ [24]

 2) Download Python 3.7 version (around 500 MB)

 3) Once installed, launch the Anaconda Navigator (search by clicking the windows button)

 4) Run the required Application (Jupyter, Spyder, etc.)

Make sure you constantly update the entire Anaconda distribution as it takes care of updating all the modules and dependencies inside (For more on installation, go to https://docs.anaconda.com/anaconda/install/windows/ for Windows version).