Add ensemble and use lexycographic order in sub-crates list

Author: relf

README.md

@@ -30,22 +30,25 @@ Where does `linfa` stand right now? [Are we learning yet?](http://www.arewelearn
 
 | Name | Purpose | Status | Category |  Notes | 
 | :--- | :--- | :---| :--- | :---| 
+| [bayes](algorithms/linfa-bayes/) | Naive Bayes | Tested | Supervised learning | Contains Bernouilli, Gaussian and Multinomial Naive Bayes |
 | [clustering](algorithms/linfa-clustering/) | Data clustering | Tested / Benchmarked  | Unsupervised learning | Clustering of unlabeled data; contains K-Means, Gaussian-Mixture-Model, DBSCAN and OPTICS | 
+| [ensemble](algorithms/linfa-ensemble/) | Ensemble methods | Tested | Supervised learning | Contains bagging |
+| [elasticnet](algorithms/linfa-elasticnet/) | Elastic Net | Tested | Supervised learning | Linear regression with elastic net constraints |
+| [ftrl](algorithms/linfa-ftrl/) | Follow The Regularized Leader - proximal | Tested  / Benchmarked | Partial fit | Contains L1 and L2 regularization. Possible incremental 
+| [hierarchical](algorithms/linfa-hierarchical/) | Agglomerative hierarchical clustering | Tested | Unsupervised learning | Cluster and build hierarchy of clusters |
+| [ica](algorithms/linfa-ica/) | Independent component analysis | Tested | Unsupervised learning | Contains FastICA implementation |
 | [kernel](algorithms/linfa-kernel/) | Kernel methods for data transformation  | Tested  | Pre-processing | Maps feature vector into higher-dimensional space| 
 | [linear](algorithms/linfa-linear/) | Linear regression | Tested  | Partial fit | Contains Ordinary Least Squares (OLS), Generalized Linear Models (GLM) | 
-| [elasticnet](algorithms/linfa-elasticnet/) | Elastic Net | Tested | Supervised learning | Linear regression with elastic net constraints |
 | [logistic](algorithms/linfa-logistic/) | Logistic regression | Tested  | Partial fit | Builds two-class logistic regression models
+| [nn](algorithms/linfa-nn/) | Nearest Neighbours & Distances | Tested / Benchmarked | Pre-processing | Spatial index structures and distance functions |
+| [pls](algorithms/linfa-pls/) | Partial Least Squares | Tested | Supervised learning | Contains PLS estimators for dimensionality reduction and regression |
+| [preprocessing](algorithms/linfa-preprocessing/) |Normalization & Vectorization| Tested / Benchmarked | Pre-processing | Contains data normalization/whitening and count 
 | [reduction](algorithms/linfa-reduction/) | Dimensionality reduction | Tested | Pre-processing | Diffusion mapping, Principal Component Analysis (PCA), Random projections |
-| [trees](algorithms/linfa-trees/) | Decision trees | Tested / Benchmarked  | Supervised learning | Linear decision trees
 | [svm](algorithms/linfa-svm/) | Support Vector Machines | Tested  | Supervised learning | Classification or regression analysis of labeled datasets | 
-| [hierarchical](algorithms/linfa-hierarchical/) | Agglomerative hierarchical clustering | Tested | Unsupervised learning | Cluster and build hierarchy of clusters |
-| [bayes](algorithms/linfa-bayes/) | Naive Bayes | Tested | Supervised learning | Contains Gaussian Naive Bayes |
-| [ica](algorithms/linfa-ica/) | Independent component analysis | Tested | Unsupervised learning | Contains FastICA implementation |
-| [pls](algorithms/linfa-pls/) | Partial Least Squares | Tested | Supervised learning | Contains PLS estimators for dimensionality reduction and regression |
+| [trees](algorithms/linfa-trees/) | Decision trees | Tested / Benchmarked  | Supervised learning | Linear decision trees
 | [tsne](algorithms/linfa-tsne/) | Dimensionality reduction| Tested | Unsupervised learning | Contains exact solution and Barnes-Hut approximation t-SNE |
-| [preprocessing](algorithms/linfa-preprocessing/) |Normalization & Vectorization| Tested / Benchmarked | Pre-processing | Contains data normalization/whitening and count vectorization/tf-idf |
-| [nn](algorithms/linfa-nn/) | Nearest Neighbours & Distances | Tested / Benchmarked | Pre-processing | Spatial index structures and distance functions |
-| [ftrl](algorithms/linfa-ftrl/) | Follow The Regularized Leader - proximal | Tested  / Benchmarked | Partial fit | Contains L1 and L2 regularization. Possible incremental update |
+vectorization/tf-idf |
+update |
 
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