Update README.md

Author: krzjoa

README.md

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 * [scikit-multilearn](https://github.com/scikit-multilearn/scikit-multilearn) - Multi-label classification for python. <img height="20" src="img/sklearn_big.png" alt="sklearn">
 * [seqlearn](https://github.com/larsmans/seqlearn) - Sequence classification toolkit for Python. <img height="20" src="img/sklearn_big.png" alt="sklearn">
 * [pystruct](https://github.com/pystruct/pystruct) - Simple structured learning framework for Python. <img height="20" src="img/sklearn_big.png" alt="sklearn">
-* [sklearn-expertsys](https://github.com/tmadl/sklearn-expertsys) - Highly interpretable classifiers for scikit learn, producing easily understood decision rules instead of black box models. <img height="20" src="img/sklearn_big.png" alt="sklearn">
+* [sklearn-expertsys](https://github.com/tmadl/sklearn-expertsys) - Highly interpretable classifiers for scikit learn. <img height="20" src="img/sklearn_big.png" alt="sklearn">
 * [RuleFit](https://github.com/christophM/rulefit) - Implementation of the rulefit. <img height="20" src="img/sklearn_big.png" alt="sklearn">
 * [metric-learn](https://github.com/all-umass/metric-learn) - Metric learning algorithms in Python. <img height="20" src="img/sklearn_big.png" alt="sklearn">
 * [pyGAM](https://github.com/dswah/pyGAM) - Generalized Additive Models in Python.