Python | Create Test DataSets using Sklearn
Python’s Sklearn library provides a great sample dataset generator which will help you to create your own custom dataset. It’s fast and very easy to use. Following are the types of samples it provides.
For all the above methods you need to import sklearn.datasets.samples_generator.
# importing libraries from sklearn.datasets.samples_generator # matplotlib for ploting from matplotlib import pyplot as plt from matplotlib import style |
chevron_right
filter_none
sklearn.datasets.make_blobs
# Creating Test DataSets using sklearn.datasets.make_blobs from sklearn.datasets.samples_generator import make_blobs from matplotlib import pyplot as plt from matplotlib import style style.use("fivethirtyeight") X, y = make_blobs(n_samples = 100, centers = 3, cluster_std = 1, n_features = 2) plt.scatter(X[:, 0], X[:, 1], s = 40, color = 'g') plt.xlabel("X") plt.ylabel("Y") plt.show() plt.clf() |
chevron_right
filter_none
Output:
make_blobs with 3 centers
sklearn.datasets.make_moon
# Creating Test DataSets using sklearn.datasets.make_moon from sklearn.datasets.samples_generator import make_moon from matplotlib import pyplot as plt from matplotlib import style X, y = make_moons(n_samples = 1000, noise = 0.1) plt.scatter(X[:, 0], X[:, 1], s = 40, color ='g') plt.xlabel("X") plt.ylabel("Y") plt.show() plt.clf() |
chevron_right
filter_none
Output:
make_moons with 1000 data points
sklearn.datasets.make_circle
# Creating Test DataSets using sklearn.datasets.make_circles from sklearn.datasets.samples_generator import make_circles from matplotlib import pyplot as plt from matplotlib import style style.use("fivethirtyeight") X, y = make_circles(n_samples = 100, noise = 0.02) plt.scatter(X[:, 0], X[:, 1], s = 40, color ='g') plt.xlabel("X") plt.ylabel("Y") plt.show() plt.clf() |
chevron_right
filter_none
Output:
make _circle with 100 data points
Recommended Posts:
- Learning Model Building in Scikit-learn : A Python Machine Learning Library
- Classifying data using Support Vector Machines(SVMs) in Python
- Introduction To Machine Learning using Python
- Tokenize text using NLTK in python
- Removing stop words with NLTK in Python
- How to get synonyms/antonyms from NLTK WordNet in Python?
- Convert Text to Speech in Python
- Phyllotaxis pattern in Python | A unit of Algorithmic Botany
- Turing Test in Artificial Intelligence
- Data Preprocessing for Machine learning in Python
- Decision tree implementation using Python
- Plotting graph using Seaborn | Python
- Analysis of test data using K-Means Clustering in Python
- R vs Python in Datascience
- Python | Named Entity Recognition (NER) using spaCy
If you like GeeksforGeeks and would like to contribute, you can also write an article using contribute.geeksforgeeks.org or mail your article to contribute@geeksforgeeks.org. See your article appearing on the GeeksforGeeks main page and help other Geeks.
Please Improve this article if you find anything incorrect by clicking on the "Improve Article" button below.
