Adding clustering 5 models inside single_model_dict #32

[Tihsrah]

PR tagged with #32

I have added 5 clustering models in automl -> models.py . Name of the clustering models are as follows: AffinityPropagation AgglomerativeClustering Birch DBSCAN KMeans . DESCRIPTION AffinityPropagation - It involves finding a set of exemplars that best summarize the data. It takes as input measures of similarity between pairs of data points. Real-valued messages are exchanged between data points until a high-quality set of exemplars and corresponding clusters gradually emerges . AgglomerativeClustering- It involves merging examples until the desired number of clusters is achieved.It is implemented via the class AgglomerativeClustering and the main configuration to tune is the “n_clusters” set, an estimate of the number of clusters in the data, e.g. 2. . BIRCH -BIRCH Clustering involves constructing a tree structure from which cluster centroids are extracted. main configuration to tune is the “threshold” and “n_clusters” hyperparameters, the latter of which provides an estimate of the number of clusters. . DBSCAN Clustering involves finding high-density areas in the domain and expanding those areas of the feature space around them as clusters. the main configuration to tune is the “eps” and “min_samples” hyperparameters. . KMEANS -the main configuration to tune is the “n_clusters” hyperparameter set to the estimated number of clusters in the data.

[sagnik1511]

Update the description properly so that you'll get points.

[Tihsrah]

done

[sagnik1511]

Thanks! Merged