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6.6. Random Projection

Scikit-learn User Guide

The sklearn.random_projection module implements a simple and computationally efficient way to reduce the dimensionality of the data by trading a controlled amount of accuracy (as additional varianc......

Random Projection And Its Role In Data Science

Towards Data Science

Often in Data Science, it can be very difficult to work with features that are very high-dimensional. This is because data in high-dimensions cannot be analyzed by computers or humans because it is…

Random Projection in Python

Towards Data Science

Dimension reduction is usually a must-to-do preprocessing when dealing with big data. One of the most widely used methods is Principal Component Analysis (PCA), but the major shortcoming of PCA is…

Random Projection Neural Networks

Analytics Vidhya

Welcome to the Papers Implemented Series. In this series, I am going to implement some very interesting papers in pytorch and try to explain the paper’s content in simple terms.

The Johnson-Lindenstrauss bound for embedding with random projections

Scikit-learn Examples

The Johnson-Lindenstrauss bound for embedding with random projections The Johnson-Lindenstrauss lemma states that any high dimensional dataset can be randomly projected into a lower dimensional Euclid...

Save Computation Time for Clustering using Random Projections

Analytics Vidhya

From time to time, you have to deal with datasets with a large number of features. Here you can learn how to reduce them in an easy way.

An Analysis of Shingling and Random Projection Algorithms

Level Up Coding

In a previous article, we discussed sequence similarity through Levenshtein distance and evaluated that at O(m*n). As we look to apply this algorithm to data sets of a larger size and scale, it…

Behind the scenes on the Fast Random Projection algorithm for generating graph embeddings

Towards Data Science

The vast majority of data science and machine learning models rely on creating a vector, or embedding, of your data. Some of these embeddings naturally create themselves. For example, for numerical…

“Interesting” Projections — Where PCA Fails.

Towards Data Science

Most data scientists are familiar with principal components analysis (PCA) as an exploratory data analysis tool. A recap for the uninitiated: researchers often use PCA for dimensionality reduction in…...

Back Projection

OpenCV Tutorial

In this tutorial you will learn: Theory What is Back Projection? How does it work? Code C++ Java Python Explanation C++ Java Python C++ Java Python C++ Java Python C++ Java Python C++ Java Python C++ ...

The World Map with Many Faces — Map Projections

Towards Data Science

Member-only story The World Map with Many Faces — Map Projections Milan Janosov · Follow Published in Towards Data Science · 5 min read · Oct 1 -- 1 Share In this short piece, I review what map projec...

Random

Codecademy

The Random class is present in the java.util package. It is used to generate random values or streams of random values of specific data types. Usage The Random class can be accessed by importing it as...