Softmax regression sklearn

**Softmax****Regression**(synonyms: Multinomial Logistic, ... Scikit-learn is an open-source Python package. It is a library that provides a set of selected tools for ML and statistical modeling. It includes**regression**, classification, dimensionality reduction, and clustering. It is properly documented and easy to install and use in a few simple steps.**Softmax****Regression**(synonyms: Multinomial Logistic, Maximum Entropy Classifier, or just Multi-class Logistic**Regression**) is a generalization of logistic**regression**that we can use for multi-class classification (under the assumption that the classes are mutually exclusive). In contrast, we use the (standard) Logistic**Regression**model in binary ...- If we have > 2 classes, then our classification problem would become Multinomial Logistic
**Regression**, or more simply, a**Softmax**classifier. With that said, open up a new file, name it**softmax**.py, and insert the following code: # import the necessary packages from**sklearn**.preprocessing import LabelEncoder from**sklearn**.linear_model import SGDClassifier - Demo for using xgboost with
**sklearn**; Demo for obtaining leaf index; This script demonstrate how to access the eval metrics; Demo for gamma**regression**; Demo for boosting from prediction; Demo for using feature weight to change column sampling; Demo for accessing the xgboost eval metrics by using**sklearn**interface; Demo for GLM