http:\/\/www.nonlinear.com\/support\/progenesis\/lc-ms\/faq\/v4.1\/pca.aspx<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"Overview for Principal Components Analysis https:\/\/support.minitab.com\/en-us\/minitab\/18\/help-and-how-to\/modeling-statistics\/multivariate\/how-to\/principal-components\/before-you-start\/overview\/ " The goal of principal components analysis is to explain the maximum amount of variance with the fewest number of principal components." Interpret the key results for Principal Components Analysis https:\/\/support.minitab.com\/en-us\/minitab\/18\/help-and-how-to\/modeling-statistics\/multivariate\/how-to\/principal-components\/interpret-the-results\/key-results\/ Interpret all statistics and graphs for Principal Components Analysis https:\/\/support.minitab.com\/en-us\/minitab\/18\/help-and-how-to\/modeling-statistics\/multivariate\/how-to\/principal-components\/interpret-the-results\/all-statistics-and-graphs\/ Methods and formulas for Principal Components Analysis https:\/\/support.minitab.com\/en-us\/minitab\/18\/help-and-how-to\/modeling-statistics\/multivariate\/how-to\/principal-components\/methods-and-formulas\/methods-and-formulas\/ … <\/p>\n
Continue reading<\/a><\/p>\n","protected":false},"author":2,"featured_media":0,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_jetpack_memberships_contains_paid_content":false,"footnotes":""},"categories":[1910,182],"tags":[],"class_list":["post-14860","post","type-post","status-publish","format-standard","hentry","category-ai-ml-ds-rl-dl-nn-nlp-data-mining-optimization","category---blog","item-wrap"],"jetpack_featured_media_url":"","jetpack_sharing_enabled":true,"jetpack-related-posts":[{"id":14819,"url":"http:\/\/bangla.sitestree.com\/?p=14819","url_meta":{"origin":14860,"position":0},"title":"Tools : Regression: Data Science and Analytics:","author":"Sayed","date":"June 19, 2019","format":false,"excerpt":"Online Multiple Linear Regression http:\/\/www.xuru.org\/rt\/mlr.asp --- How to Identify the Most Important Predictor Variables in Regression Models https:\/\/blog.minitab.com\/blog\/adventures-in-statistics-2\/how-to-identify-the-most-important-predictor-variables-in-regression-models --- How to Interpret Regression Analysis Results: P-values and Coefficients https:\/\/blog.minitab.com\/blog\/adventures-in-statistics-2\/how-to-interpret-regression-analysis-results-p-values-and-coefficients --- Why You Need to Check Your Residual Plots for Regression Analysis: Or, To Err is Human, To Err Randomly is\u2026","rel":"","context":"In "AI ML DS RL DL NN NLP Data Mining Optimization"","block_context":{"text":"AI ML DS RL DL NN NLP Data Mining Optimization","link":"http:\/\/bangla.sitestree.com\/?cat=1910"},"img":{"alt_text":"","src":"","width":0,"height":0},"classes":[]},{"id":16619,"url":"http:\/\/bangla.sitestree.com\/?p=16619","url_meta":{"origin":14860,"position":1},"title":"Math\/Stat\/CS\/DS Topics that you need to know (with Cognitive, Psychomotor, Affective domain skills) to become a true and great Data Scientist","author":"Sayed","date":"January 7, 2020","format":false,"excerpt":"\"The core topics are cross-validation, shrinkage methods (ridge regression, the LASSO, etc.), neural networks, gradient boosting, separating hyperplanes, support vector machines, basis expansion and regularization (e.g., smoothing splines, wavelet smoothing, kernel smoothing), generalized additive models, bump hunting, multivariate adaptive regression splines (MARS), self-organizing maps, mixture model-based clustering, ensemble learning, and\u2026","rel":"","context":"In "Math and Statistics for Data Science, and Engineering"","block_context":{"text":"Math and Statistics for Data Science, and Engineering","link":"http:\/\/bangla.sitestree.com\/?cat=1908"},"img":{"alt_text":"","src":"","width":0,"height":0},"classes":[]},{"id":14820,"url":"http:\/\/bangla.sitestree.com\/?p=14820","url_meta":{"origin":14860,"position":2},"title":"How to Interpret your Regression Results","author":"Sayed","date":"June 19, 2019","format":false,"excerpt":"How to Interpret your Regression Results Goal: How to Identify the Most Important Predictor Variables in Regression Models https:\/\/blog.minitab.com\/blog\/adventures-in-statistics-2\/how-to-identify-the-most-important-predictor-variables-in-regression-models --- --- How to Interpret Regression Analysis Results: P-values and Coefficients https:\/\/blog.minitab.com\/blog\/adventures-in-statistics-2\/how-to-interpret-regression-analysis-results-p-values-and-coefficients --- Regression Analysis: How to Interpret the Constant (Y Intercept) https:\/\/blog.minitab.com\/blog\/adventures-in-statistics-2\/regression-analysis-how-to-interpret-the-constant-y-intercept --- How to Compare Regression Slopes: How to\u2026","rel":"","context":"In "\u09ac\u09cd\u09b2\u0997 \u0964 Blog"","block_context":{"text":"\u09ac\u09cd\u09b2\u0997 \u0964 Blog","link":"http:\/\/bangla.sitestree.com\/?cat=182"},"img":{"alt_text":"","src":"","width":0,"height":0},"classes":[]},{"id":25041,"url":"http:\/\/bangla.sitestree.com\/?p=25041","url_meta":{"origin":14860,"position":3},"title":"How to Interpret your Regression Results #Root","author":"Author-Check- Article-or-Video","date":"April 15, 2021","format":false,"excerpt":"How to Interpret your Regression Results Goal: How to Identify the Most Important Predictor Variables in Regression Models https:\/\/blog.minitab.com\/blog\/adventures-in-statistics-2\/how-to-identify-the-most-important-predictor-variables-in-regression-models --- --- How to Interpret Regression Analysis Results: P-values and Coefficients https:\/\/blog.minitab.com\/blog\/adventures-in-statistics-2\/how-to-interpret-regression-analysis-results-p-values-and-coefficients --- Regression Analysis: How to Interpret the Constant (Y Intercept) https:\/\/blog.minitab.com\/blog\/adventures-in-statistics-2\/regression-analysis-how-to-interpret-the-constant-y-intercept --- How to Compare Regression Slopes: How to\u2026","rel":"","context":"In "FromSitesTree.com"","block_context":{"text":"FromSitesTree.com","link":"http:\/\/bangla.sitestree.com\/?cat=1917"},"img":{"alt_text":"","src":"","width":0,"height":0},"classes":[]},{"id":14825,"url":"http:\/\/bangla.sitestree.com\/?p=14825","url_meta":{"origin":14860,"position":4},"title":"Machine Learning: Apply PCA on Datasets and Related","author":"Sayed","date":"June 22, 2019","format":false,"excerpt":"FactorAnalyzer https:\/\/github.com\/EducationalTestingService\/factor_analyzer --- sruti-jain\/Marketing-Analysis-for-Hotel-Chain-website https:\/\/github.com\/sruti-jain\/Marketing-Analysis-for-Hotel-Chain-website --- Understanding PCA (Principal Component Analysis) with Python https:\/\/towardsdatascience.com\/dive-into-pca-principal-component-analysis-with-python-43ded13ead21 The code for the most part will work though it used an earlier version of Python You will need module: StandardScaler Otherwise you might find the code below to be useful: [# ref: https:\/\/python-for-multivariate-analysis.readthedocs.io\/a_little_book_of_python_for_multivariate_analysis.html] import sklearn\u2026","rel":"","context":"In "AI ML DS RL DL NN NLP Data Mining Optimization"","block_context":{"text":"AI ML DS RL DL NN NLP Data Mining Optimization","link":"http:\/\/bangla.sitestree.com\/?cat=1910"},"img":{"alt_text":"","src":"","width":0,"height":0},"classes":[]},{"id":16218,"url":"http:\/\/bangla.sitestree.com\/?p=16218","url_meta":{"origin":14860,"position":5},"title":"Resources including Research papers for Dietary pattern and Kidney Diseases","author":"Sayed","date":"September 26, 2019","format":false,"excerpt":"Resources including Research papers for Dietary pattern and Kidney Diseases Also, includes topics related to data analysis [1] The National Institute of Diabetes and Digestive and Kidney Diseases. What Is Chronic Kidney Disease? https:\/\/www.niddk.nih.gov\/health-information\/kidney-disease\/chronic-kidney-disease-ckd\/what-is-chronic-kidney-disease [2] Jaimon T. K., Suetonia C. P., Shu N. W., Marinella R., Juan-Jesus C., Katrina L.\u2026","rel":"","context":"In "\u09ac\u09cd\u09b2\u0997 \u0964 Blog"","block_context":{"text":"\u09ac\u09cd\u09b2\u0997 \u0964 Blog","link":"http:\/\/bangla.sitestree.com\/?cat=182"},"img":{"alt_text":"","src":"","width":0,"height":0},"classes":[]}],"_links":{"self":[{"href":"http:\/\/bangla.sitestree.com\/index.php?rest_route=\/wp\/v2\/posts\/14860","targetHints":{"allow":["GET"]}}],"collection":[{"href":"http:\/\/bangla.sitestree.com\/index.php?rest_route=\/wp\/v2\/posts"}],"about":[{"href":"http:\/\/bangla.sitestree.com\/index.php?rest_route=\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"http:\/\/bangla.sitestree.com\/index.php?rest_route=\/wp\/v2\/users\/2"}],"replies":[{"embeddable":true,"href":"http:\/\/bangla.sitestree.com\/index.php?rest_route=%2Fwp%2Fv2%2Fcomments&post=14860"}],"version-history":[{"count":1,"href":"http:\/\/bangla.sitestree.com\/index.php?rest_route=\/wp\/v2\/posts\/14860\/revisions"}],"predecessor-version":[{"id":16824,"href":"http:\/\/bangla.sitestree.com\/index.php?rest_route=\/wp\/v2\/posts\/14860\/revisions\/16824"}],"wp:attachment":[{"href":"http:\/\/bangla.sitestree.com\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=14860"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"http:\/\/bangla.sitestree.com\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=14860"},{"taxonomy":"post_tag","embeddable":true,"href":"http:\/\/bangla.sitestree.com\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=14860"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}