principal-component-analysis-pca | Topic

Topic: "principal-component-analysis-pca"

alifrmf/Country-Profiling-Using-PCA-and-Clustering

Unsupervised Machine Learning Analysis Using Clustering Model

Language: Jupyter Notebook - Size: 16 MB - Last synced at: over 1 year ago - Pushed at: almost 2 years ago - Stars: 13 - Forks: 1

kennethleungty/Principal-Component-Regression

Principal Component Regression - Clearly Explained and Implemented

Language: Jupyter Notebook - Size: 1.04 MB - Last synced at: 28 days ago - Pushed at: about 3 years ago - Stars: 12 - Forks: 5

namanUIUC/NonlinearComponentAnalysis

Application of principal component analysis capturing non-linearity in the data using kernel approach

Language: Jupyter Notebook - Size: 27.7 MB - Last synced at: almost 2 years ago - Pushed at: over 6 years ago - Stars: 8 - Forks: 4

iAmKankan/Data-Gathering-And-Preprocessing

Tutorial- data Pre-processing

Language: Jupyter Notebook - Size: 13.1 MB - Last synced at: about 1 month ago - Pushed at: over 2 years ago - Stars: 3 - Forks: 0

paocarvajal1912/Crypto_Clustering

Uses K-Means unsupervised machine learning algorithm and Principal Component Analysis to cluster cryptocurrencies based on performance in selected periods.

Language: Jupyter Notebook - Size: 5.16 MB - Last synced at: 7 months ago - Pushed at: over 2 years ago - Stars: 3 - Forks: 0

astonglen/AirBnb-Price-Prediction

The ability to predict prices and features affecting the appraisal of property can be a powerful tool in such a cash intensive market for a lessor. Additionally, a predictor that forecasts the number of reviews a specific listing will get may be helpful in examining elements that affect a property's popularity.

Language: Jupyter Notebook - Size: 6.76 MB - Last synced at: 12 months ago - Pushed at: 12 months ago - Stars: 1 - Forks: 0

SohhamSeal/Fisher-Faces

Explore facial recognition through an advanced Python implementation featuring Linear Discriminant Analysis (LDA). This repository provides a comprehensive resource, including algorithmic steps, specific ROI code and thorough testing segments, offering professionals a robust framework for mastering and applying LDA in real-world scenarios.

Language: Jupyter Notebook - Size: 77.2 MB - Last synced at: 2 months ago - Pushed at: about 1 year ago - Stars: 1 - Forks: 0

burning-river/arxiv_topic_modeling

Language: Jupyter Notebook - Size: 29.2 MB - Last synced at: over 1 year ago - Pushed at: about 4 years ago - Stars: 1 - Forks: 0

harshit37/Dimensionality-Reduction-using-PCA-LDA-and-t-SNE

Analysing different dimensionality reduction techniques and svm

Language: Jupyter Notebook - Size: 1.96 MB - Last synced at: about 2 years ago - Pushed at: almost 5 years ago - Stars: 1 - Forks: 0

Relostar-Devil/Bath-Body-Works-Marketing-Analytics-and-Segmentation

Positioning and segmentation analysis of Bath & Body Works using perceptual mapping, consumer preference modeling, and market simulation techniques. Utilizes PCA-based perceptual maps, K-means clustering, and first-choice share of preference models via Enginius. Provides brand differentiation & market alignment.

Size: 0 Bytes - Last synced at: about 1 month ago - Pushed at: about 1 month ago - Stars: 0 - Forks: 0

fadzy/Mtech-mini-projects

here you find a mix of projects l worked on during my studies

Language: Jupyter Notebook - Size: 3.35 MB - Last synced at: 2 months ago - Pushed at: 2 months ago - Stars: 0 - Forks: 0

Ojas-Arora/Principal-Component-Analysis

Principal Component Analysis (PCA) is a powerful dimensionality reduction technique used in data analysis and machine learning. 🌟 It transforms a dataset into a set of linearly uncorrelated variables called principal components, which capture the most variance in the data. 📉

Language: Jupyter Notebook - Size: 2.46 MB - Last synced at: 2 months ago - Pushed at: 6 months ago - Stars: 0 - Forks: 0

NotTheStallion/PCA3D-and-from-scratchPrincipal-Component-Analysis

In this project, I will be implementing Principal Component Analysis (PCA) from scratch on an ecological footprint consummation database for countries and a three-dimensional scale using a movie database. The goal of this project is to gain a deeper understanding of PCA and to demonstrate its capabilities in exploring complex datasets.

Language: Jupyter Notebook - Size: 11.7 KB - Last synced at: 2 months ago - Pushed at: about 1 year ago - Stars: 0 - Forks: 0

Xin-Bu/Dram_shop_PCA

Applies Principal Component Analysis (PCA) to dimensionality reduction using Python, SQL, and GBQ.

Language: Jupyter Notebook - Size: 178 KB - Last synced at: over 1 year ago - Pushed at: over 1 year ago - Stars: 0 - Forks: 0

AjmalSarwary/Preprocessing

Data prepration and preprocessing for predictive modeling with SAS and Python

Language: Jupyter Notebook - Size: 951 KB - Last synced at: over 1 year ago - Pushed at: almost 2 years ago - Stars: 0 - Forks: 0

AjmalSarwary/BRENT-Model

Predictive Model for BRENT price movements

Language: Jupyter Notebook - Size: 106 KB - Last synced at: over 1 year ago - Pushed at: almost 2 years ago - Stars: 0 - Forks: 0

MihaiTudor26/Principal-Component-Analysis

Language: Jupyter Notebook - Size: 216 KB - Last synced at: almost 2 years ago - Pushed at: almost 2 years ago - Stars: 0 - Forks: 0

Aziz-s99/absenteeism_analysis_classification

The database was created with records of absenteeism at work from July 2007 to July 2010 at a courier company in Brazil. The objective here is to predict for each new individual, whether he is going to be absent for more than 3 hours or no (3 hours is the median for the absenteeism hours).

Size: 764 KB - Last synced at: almost 2 years ago - Pushed at: almost 2 years ago - Stars: 0 - Forks: 0