@@ -21,19 +21,19 @@ This paper and code will help industrial users, data analysts, and researchers t
2121## Implementation
2222Sample code for hyper-parameter optimization implementation for machine learning algorithms is provided in this repository.
2323
24- ** Sample code for Regression problems**
24+ ### Sample code for Regression problems
2525[ HPO_Regression.ipynb] ( https://github.com/LiYangHart/Hyperparameter-Optimization-of-Machine-Learning-Algorithms/blob/master/HPO_Regression.ipynb )
26- Dataset used: [ Boston-Housing] ( https://scikit-learn.org/stable/modules/generated/sklearn.datasets.load_boston.html )
27- ** Sample code for Classification problems**
26+ ** Dataset used:** [ Boston-Housing] ( https://scikit-learn.org/stable/modules/generated/sklearn.datasets.load_boston.html )
27+ ### Sample code for Classification problems
2828[ HPO_Classification.ipynb] ( https://github.com/LiYangHart/Hyperparameter-Optimization-of-Machine-Learning-Algorithms/blob/master/HPO_Classification.ipynb )
29- Dataset used: [ MNIST] ( https://scikit-learn.org/stable/modules/generated/sklearn.datasets.load_digits.html#sklearn.datasets.load_digits )
29+ ** Dataset used:** [ MNIST] ( https://scikit-learn.org/stable/modules/generated/sklearn.datasets.load_digits.html#sklearn.datasets.load_digits )
3030
31- ** Machine learning algorithms used: **
31+ ### Machine Learning Algorithms
3232* Random forest (RF)
3333* Support vector machine (SVM)
3434* K-nearest neighbor (KNN)
3535
36- ** HPO algorithms used: **
36+ ### HPO Algorithms
3737* Grid search
3838* Random search
3939* Hyperband
@@ -42,15 +42,15 @@ Dataset used: [MNIST](https://scikit-learn.org/stable/modules/generated/sklearn.
4242* Particle swarm optimization (PSO)
4343* Genetic algorithm (GA).
4444
45- ** Python libraries requirements **
45+ ### Requirements
4646* Python 3.5
47- * scikit-learn
48- * hyperband
49- * scikit-optimize
50- * hyperopt
51- * optunity
52- * DEAP
53- * TPOT
47+ * [ scikit-learn] ( https://scikit-learn.org/stable/ )
48+ * [ hyperband] ( https://github.com/thuijskens/scikit-hyperband )
49+ * [ scikit-optimize] ( https://github.com/scikit-optimize/scikit-optimize )
50+ * [ hyperopt] ( https://github.com/hyperopt/hyperopt )
51+ * [ optunity] ( https://github.com/claesenm/optunity )
52+ * [ DEAP] ( https://github.com/DEAP/deap )
53+ * [ TPOT] ( https://github.com/EpistasisLab/tpot )
5454
5555## Citation
5656If you find this repository useful in your research, please cite:
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