How to Create simulated data for clustering in Python?

How to Create simulated data for clustering in Python?

How to Create simulated data for clustering in Python?

This recipe helps you Create simulated data for clustering in Python

This data science python source code does the following: 1.Creates custom clustering types datasets 2. How to use parameters related to clustering in "make_blob" 3. Obtaining the features, classes and the target variable.
In [1]:
## How to Create simulated data for clustering in Python 
def Kickstarter_Example_24():
    print(format('How to Create simulated data for clustering in Python', '*^82'))

    # Load libraries
    from sklearn.datasets import make_blobs
    import matplotlib.pyplot as plt
    import pandas as pd

    # Make the features (X) and output (y) with 200 samples,
    features, clusters = make_blobs(n_samples = 2000,
                  n_features = 10, centers = 5,
                  # with .5 cluster standard deviation,
                  cluster_std = 0.4,
                  shuffle = True)

    # View the first five observations and their 10 features
    print("Feature Matrix: ");
    print(pd.DataFrame(features, columns=['Feature 1', 'Feature 2', 'Feature 3',
         'Feature 4', 'Feature 5', 'Feature 6', 'Feature 7', 'Feature 8',
         'Feature 9', 'Feature 10']).head())

    # Create a scatterplot of the first and second features
    plt.scatter(features[:,0], features[:,1])

    # Show the scatterplot

**************How to Create simulated data for clustering in Python***************

Feature Matrix:
   Feature 1  Feature 2  Feature 3  Feature 4  Feature 5  Feature 6  \
0  -5.301777  -0.288487   4.426895  -7.346082   0.841896   7.120860
1  -2.146525   5.418930  -8.526391  -3.028764  -4.153195   9.803507
2   1.560945   6.419495  -1.759591  -9.156973   8.489981   4.229867
3   6.243948  -6.006760  -9.065597   3.672920  -1.327192   5.638014
4   5.883899   7.947210  -6.298867  -6.715524   0.361343  -5.462168

   Feature 7  Feature 8  Feature 9  Feature 10
0   5.853593  -4.528930   5.301169    4.174106
1   3.005134  -7.790637   6.252099    5.263176
2  -5.721829   5.110951  -0.667662   -2.777335
3  -9.557726  -5.902056   6.441669    2.168129
4  -2.620218  -6.522848   6.959409    5.542048
<Figure size 640x480 with 1 Axes>

Relevant Projects

Human Activity Recognition Using Smartphones Data Set
In this deep learning project, you will build a classification system where to precisely identify human fitness activities.

Ensemble Machine Learning Project - All State Insurance Claims Severity Prediction
In this ensemble machine learning project, we will predict what kind of claims an insurance company will get. This is implemented in python using ensemble machine learning algorithms.

Learn to prepare data for your next machine learning project
Text data requires special preparation before you can start using it for any machine learning project.In this ML project, you will learn about applying Machine Learning models to create classifiers and learn how to make sense of textual data.

Resume parsing with Machine learning - NLP with Python OCR and Spacy
In this machine learning resume parser example we use the popular Spacy NLP python library for OCR and text classification.

Build an Image Classifier for Plant Species Identification
In this machine learning project, we will use binary leaf images and extracted features, including shape, margin, and texture to accurately identify plant species using different benchmark classification techniques.

Identifying Product Bundles from Sales Data Using R Language
In this data science project in R, we are going to talk about subjective segmentation which is a clustering technique to find out product bundles in sales data.

Mercari Price Suggestion Challenge Data Science Project
Data Science Project in Python- Build a machine learning algorithm that automatically suggests the right product prices.

Predict Census Income using Deep Learning Models
In this project, we are going to work on Deep Learning using H2O to predict Census income.

Loan Eligibility Prediction using Gradient Boosting Classifier
This data science in python project predicts if a loan should be given to an applicant or not. We predict if the customer is eligible for loan based on several factors like credit score and past history.

Data Science Project - Instacart Market Basket Analysis
Data Science Project - Build a recommendation engine which will predict the products to be purchased by an Instacart consumer again.