Supervised learning is the machine learning task of inferring a function from labeled training data. The training data consist of a set of training examples. In supervised learning, each example is a pair consisting of an input object (typically a vector) and a desired output value (also called the supervisory signal). A supervised learning algorithm analyzes the training data and produces an inferred function, which can be used for mapping new examples.
Questions tagged [supervised-learning]
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Which is a good choice LDA or PCA for feature reduction in the supervised learning model?
PCA -> Unsupervised Model or use for supervise learning too
LDA -> supervise Model
Both used for the feature reduction.
Which is batter LDA or PCA for supervising learning feature reduction and why?
Data-set: It is very famous data-set of wine to…

Sohaib Aslam
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Is predicting number of sales a Regression or Classification problem?
I am a Machine Learning beginner who is currently doing Andrew Ng's Machine Learning course on Coursera. In the lecture, he asked a simple question: Would you call the following a classification or regression problem?
You have a large inventory of…

Muthuraja Palaniappan
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