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3 changes: 1 addition & 2 deletions README.md
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Expand Up @@ -6,8 +6,7 @@ scale. The implementation are heavily based on [scikit-learn](www.scikit-learn.o


## 1. Stacked_ensemble
Demonstrate how to use integrated or separate stacking ensemble model for different Multi-Layer Perceptron model for simple multi-class classification probelm. The notebook uses
sklearn datasets, tensorflow models and logistic regression form sklearn.linear model
In this notebook, we will explore how to implement stacking ensemble models for multi-class classification problems using both integrated and separate approaches. We will use popular machine learning libraries such as Scikit-learn and TensorFlow to create various Multi-Layer Perceptron models, and also apply logistic regression from Scikit-learn's linear model to compare their performance. The datasets used for this exercise will be provided by Scikit-learn, and we will demonstrate step-by-step instructions for each approach.

## 2. Ensemble Regressors
Test different estimators for building ensembles trained sequentially to reduce the bias and variace of the the combined estimator. The advantage is that the individual weak models
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