Principal Component Analysis — Unsupervised Learning Model
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Principal Component Analysis — Unsupervised Learning ModelLearn how to train and evaluate an unsupervised machine learning model — principal component analysis in this article by Jillur Quddus, a lead technical architect, polyglot software engineer and data scientist.There are numerous real-world use cases, where the number of features available, which may potentially be used to train a model, is very large. A common example is economic data and using its constituents, stock price data, employment data, banking data, industrial data, and housing data together to predict the gross domestic product (GDP). Such types of data are said to have high dimensionality. Though they offer numerous features that can be used to model a given use case, high-dimensional datasets increase the computational (...)
#machine-learning #apache-spark #component-analysis #principal-component #unsupervised-learning