#DimensionalityReduction

[damilola-doodles]

🟨Project Title: Robust Cross-Domain Data Normalization and Dimensionality Reduction Pipeline.⭐😊

ai-ml-ds-preprocessing-dimensionality-reduction-017 Filename: data_normalization_reduction_pipeline.py Timestamp: Mon Jun 02 2025 19:36:18 GMT+0000 (Coordinated Universal Time) Problem Domain:Data Preprocessing, Feature Engineering, Exploratory Data Analysis (EDA), Machine Learning Pipeline Development, Data Integration. Project Description:This project focuses on creating a flexible and…

[dammyanimation]

🟨Project Title: Robust Cross-Domain Data Normalization and Dimensionality Reduction Pipeline.⭐😊

ai-ml-ds-preprocessing-dimensionality-reduction-017 Filename: data_normalization_reduction_pipeline.py Timestamp: Mon Jun 02 2025 19:36:18 GMT+0000 (Coordinated Universal Time) Problem Domain:Data Preprocessing, Feature Engineering, Exploratory Data Analysis (EDA), Machine Learning Pipeline Development, Data Integration. Project Description:This project focuses on creating a flexible and…

[damilola-ai-automation]

🟨Project Title: Robust Cross-Domain Data Normalization and Dimensionality Reduction Pipeline.⭐😊

ai-ml-ds-preprocessing-dimensionality-reduction-017 Filename: data_normalization_reduction_pipeline.py Timestamp: Mon Jun 02 2025 19:36:18 GMT+0000 (Coordinated Universal Time) Problem Domain:Data Preprocessing, Feature Engineering, Exploratory Data Analysis (EDA), Machine Learning Pipeline Development, Data Integration. Project Description:This project focuses on creating a flexible and…

[damilola-warrior-mindset]

🟨Project Title: Robust Cross-Domain Data Normalization and Dimensionality Reduction Pipeline.⭐😊

ai-ml-ds-preprocessing-dimensionality-reduction-017 Filename: data_normalization_reduction_pipeline.py Timestamp: Mon Jun 02 2025 19:36:18 GMT+0000 (Coordinated Universal Time) Problem Domain:Data Preprocessing, Feature Engineering, Exploratory Data Analysis (EDA), Machine Learning Pipeline Development, Data Integration. Project Description:This project focuses on creating a flexible and…

[damilola-moyo]

🟨Project Title: Robust Cross-Domain Data Normalization and Dimensionality Reduction Pipeline.⭐😊

ai-ml-ds-preprocessing-dimensionality-reduction-017 Filename: data_normalization_reduction_pipeline.py Timestamp: Mon Jun 02 2025 19:36:18 GMT+0000 (Coordinated Universal Time) Problem Domain:Data Preprocessing, Feature Engineering, Exploratory Data Analysis (EDA), Machine Learning Pipeline Development, Data Integration. Project Description:This project focuses on creating a flexible and…

[expertlytics]

PCA is a dimensionality reduction technique that reduces the dimensionality of volume datasets by transforming a large set of variables into a smaller one that still contains most of the information in the large set. The main objective of PCA is to simplify model features into fewer components to help visualize patterns in the data and to make the model run faster. Using PCA also reduces the chance of overfitting the model by eliminating features with high correlation. PCA is defined as an orthogonal linear transformation that finds mutually orthogonal directions of maximal variance. It transforms the data so that the greatest variance lies on the 1st coordinate (called the 1st Principal Component), the 2nd greatest variance on the second coordinate, and so on. PCA is sensitive to outliers in the data that produce large errors. Therefore, there is common practice to remove outliers before computing PCA.  Usually, PCA relies on a linear model. If a dataset has a pattern hidden inside it that is nonlinear, then PCA can actually steer the analysis in the complete opposite direction of progress. The results of PCA depend on the scaling of the variables. #patternrecognition #dimensionalityreduction #machinelearning #datascience https://www.instagram.com/p/CQAYUM8D8vf/?utm_medium=tumblr

[malfunkn]

This is dimensionality reduction on my classic breaks folder after segmenting and analyzing similarities. #breaks #machinelearning #artificialintelligence #coding #techno #idm #malfunkn #sampling #dimensionalityreduction http://ift.tt/2ytLPJs

[expertlytics]

#principlecomponentanalysis #pca #probabilisticpca #pcavisualization #pcaillustration #dimensionalityreduction (at United States)

[expertlytics]

#data #datascience #datascientist #datamining #datavisualization #dataviz #bigdata #bigdataanalytics #coding #statistics #probability #machinelearning #artificialintelligence #database #mathematics #math #science #research #scientist #studygram #learning #computerscience #analysis #analytics #visualization #featureengineering #математика #статистика #наука #dimensionalityreduction (at United States)

[expertlytics]

———————————————————————— Linear Discriminant Analysis (LDA) is most commonly used as dimensionality reduction technique in the pre-processing step for pattern-classification and machine learning applications. — The goal is to project a dataset onto a lower-dimensional space with good class-separability in order avoid overfitting (“curse of dimensionality”) and also reduce computational costs. — ‪The general LDA approach is very similar to a Principal Component Analysis, but in addition to finding the component axes that maximize the variance of our data (PCA), we are additionally interested in the axes that maximize the separation between multiple classes (LDA).‬ ‪—‬ So, in a nutshell, often the goal of an LDA is to project a feature space (a dataset n-dimensional samples) onto a smaller subspace. ———————————————————————— #data #bigdata #bigdataanalytics #dataanalysis #datascience #datascientist #datamining #dataprocessing #datavisualization #dataviz #machinelearning #lda #artificialintelligence #algorithm #analysis #analytics #statistics #bayesianstatistics #studygram #learning #study #science #computers #computerscience #research #predictiveanalytics #математика #физика #lineardiscriminantanalysis #dimensionalityreduction (at United States)