Update version to 0.19.0 (#767)

Author: ishii-norimi

Diff for: README.md

@@ -39,7 +39,7 @@ Download from the CDN.
 
 ```HTML
 <script type="module">
-    import dam from 'https://cdn.jsdelivr.net/npm/@ai-on-browser/data-analysis-models@0.18.0/lib/index.min.js';
+    import dam from 'https://cdn.jsdelivr.net/npm/@ai-on-browser/data-analysis-models@0.19.0/lib/index.min.js';
     // Do something
 </script>
 ```
@@ -122,10 +122,11 @@ for (let i = 0; i < n; i++) {
 | task | model |
 | ---- | ----- |
 | clustering | (Soft / Kernel / Genetic / Weighted) k-means, k-means++, k-medois, k-medians, x-means, G-means, LBG, ISODATA, Fuzzy c-means, Possibilistic c-means, Agglomerative (complete linkage, single linkage, group average, Ward's, centroid, weighted average, median), DIANA, Monothetic, Mutual kNN, Mean shift, DBSCAN, OPTICS, HDBSCAN, DENCLUE, DBCLASD, BRIDGE, CLUES, PAM, CLARA, CLARANS, BIRCH, CURE, ROCK, C2P, PLSA, Latent dirichlet allocation, GMM, VBGMM, Affinity propagation, Spectral clustering, Mountain, (Growing) SOM, GTM, (Growing) Neural gas, Growing cell structures, LVQ, ART, SVC, CAST, CHAMELEON, COLL, CLIQUE, PROCLUS, ORCLUS, FINDIT, NMF, Autoencoder |
-| classification | (Fisher's) Linear discriminant, Quadratic discriminant, Mixture discriminant, Least squares, (Multiclass / Kernel) Ridge, (Complement / Negation / Universal-set / Selective) Naive Bayes (gaussian), AODE, (Fuzzy / Weighted) k-nearest neighbor, Radius neighbor, Nearest centroid, ENN, ENaN, NNBCA, ADAMENN, DANN, IKNN, Decision tree, Random forest, Extra trees, GBDT, XGBoost, ALMA, (Aggressive) ROMMA, (Bounded) Online gradient descent, (Budgeted online) Passive aggressive, RLS, (Selective-sampling) Second order perceptron, AROW, NAROW, Confidence weighted, CELLIP, IELLIP, Normal herd, Stoptron, (Kernelized) Pegasos, MIRA, Forgetron, Projectron, Projectron++, Banditron, Ballseptron, (Multiclass) BSGD, ILK, SILK, (Multinomial) Logistic regression, (Multinomial) Probit, Ordered logistic, Ordered probit, PRank, OAP-BPM, SVM, Gaussian process, HMM, CRF, Bayesian Network, LVQ, (Average / Multiclass / Voted / Kernelized / Selective-sampling / Margin / Shifting / Budget / Tighter / Tightest) Perceptron, PAUM, RBP, ADALINE, MADALINE, MLP, LMNN |
+| classification | (Fisher's) Linear discriminant, Quadratic discriminant, Mixture discriminant, Least squares, (Multiclass / Kernel) Ridge, (Complement / Negation / Universal-set / Selective) Naive Bayes (gaussian), AODE, (Fuzzy / Weighted) k-nearest neighbor, Radius neighbor, Nearest centroid, ENN, ENaN, NNBCA, ADAMENN, DANN, IKNN, Decision tree, Random forest, Extra trees, GBDT, XGBoost, ALMA, (Aggressive) ROMMA, (Bounded) Online gradient descent, (Budgeted online) Passive aggressive, RLS, (Selective-sampling) Second order perceptron, AROW, NAROW, Confidence weighted, CELLIP, IELLIP, Normal herd, Stoptron, (Kernelized) Pegasos, MIRA, Forgetron, Projectron, Projectron++, Banditron, Ballseptron, (Multiclass) BSGD, ILK, SILK, (Multinomial) Logistic regression, (Multinomial) Probit, SVM, Gaussian process, HMM, CRF, Bayesian Network, LVQ, (Average / Multiclass / Voted / Kernelized / Selective-sampling / Margin / Shifting / Budget / Tighter / Tightest) Perceptron, PAUM, RBP, ADALINE, MADALINE, MLP, LMNN |
 | semi-supervised classification | k-nearest neighbor, Radius neighbor, Label propagation, Label spreading, k-means, GMM, S3VM, Ladder network |
 | regression | Least squares, Ridge, Lasso, Elastic net, RLS, Bayesian linear, Poisson, Least absolute deviations, Huber, Tukey, Least trimmed squares, Least median squares, Lp norm linear, SMA, Deming, Segmented, LOWESS, LOESS, spline, Naive Bayes, Gaussian process, Principal components, Partial least squares, Projection pursuit, Quantile regression, k-nearest neighbor, Radius neighbor, IDW, Nadaraya Watson, Priestley Chao, Gasser Muller, RBF Network, RVM, Decision tree, Random forest, Extra trees, GBDT, XGBoost, SVR, MLP, GMR, Isotonic, Ramer Douglas Peucker, Theil-Sen, Passing-Bablok, Repeated median |
 | interpolation | Nearest neighbor, IDW, (Spherical) Linear, Brahmagupta, Logarithmic, Cosine, (Inverse) Smoothstep, Cubic, (Centripetal) Catmull-Rom, Hermit, Polynomial, Lagrange, Trigonometric, Spline, RBF Network, Akima, Natural neighbor, Delaunay |
+| learning to rank | Ordered logistic, Ordered probit, PRank, OAP-BPM |
 | anomaly detection | Percentile, MAD, Tukey's fences, Grubbs's test, Thompson test, Tietjen Moore test, Generalized ESD, Hotelling, MT, MCD, k-nearest neighbor, LOF, COF, ODIN, LDOF, INFLO, LOCI, LoOP, RDF, LDF, KDEOS, RDOS, NOF, RKOF, ABOD, PCA, OCSVM, KDE, GMM, Isolation forest, Autoencoder, GAN |
 | dimensionality reduction | Random projection, (Dual / Kernel / Incremental / Probabilistic) PCA, GPLVM, LSA, MDS, Linear discriminant analysis, NCA, ICA, Principal curve, Sammon, FastMap, Sliced inverse regression, LLE, HLLE, MLLE, Laplacian eigenmaps, Isomap, LTSA, Diffusion map, SNE, t-SNE, UMAP, SOM, GTM, NMF, MOD, K-SVD, Autoencoder, VAE |
 | feature selection | Mutual information, Ridge, Lasso, Elastic net, Decision tree, NCA |

Diff for: package.json

@@ -1,6 +1,6 @@
 {
   "name": "@ai-on-browser/data-analysis-models",
-  "version": "0.18.0",
+  "version": "0.19.0",
   "description": "Data analysis model package without any dependencies",
   "type": "module",
   "main": "./lib/index.js",