Dummy Variables/Binary Variables - Python for Integrated Circuits - - An Online Book - |
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Python for Integrated Circuits http://www.globalsino.com/ICs/ | ||||||||
Chapter/Index: Introduction | A | B | C | D | E | F | G | H | I | J | K | L | M | N | O | P | Q | R | S | T | U | V | W | X | Y | Z | Appendix | ||||||||
================================================================================= The OneHotEncoder() performs one hot encoding. One hot encoding consists in replacing the categorical variable by a group of binary variables which take value 0 or 1, to indicate if a certain category is present in the observation. The binary variables are also known as dummy variables. Machine learning methods such as logistic regression, SVM with a linear kernel, and so on, will often require that categorical variables be converted into dummy variables. For example, a single feature Vehicle would be converted into three features, Cars, Trucks, and Pickups, one for each category in the categorical feature. The common ways to preprocess categorical features are: ============================================ Preprocessing categorical features. code:
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