Create ML Algotithms (#274)

Author: YashPame

AI and ML/ML Algotithms

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+Regression Algorithms
+•	Ordinary Least Squares Regression (OLSR)
+•	Linear Regression
+•	Logistic Regression
+•	Stepwise Regression
+•	Multivariate Adaptive Regression Splines (MARS)
+•	Locally Estimated Scatterplot Smoothing (LOESS)
+Instance-based Algorithms
+•	k-Nearest Neighbor (kNN)
+•	Learning Vector Quantization (LVQ)
+•	Self-Organizing Map (SOM)
+•	Locally Weighted Learning (LWL)
+•	Support Vector Machines (SVM)
+Regularization Algorithms
+•	Ridge Regression
+•	Least Absolute Shrinkage and Selection Operator (LASSO)
+•	Elastic Net
+•	Least-Angle Regression (LARS)
+Decision Tree Algorithms
+•	Classification and Regression Tree (CART)
+•	Iterative Dichotomiser 3 (ID3)
+•	C4.5 and C5.0 (different versions of a powerful approach)
+•	Chi-squared Automatic Interaction Detection (CHAID)
+•	Decision Stump
+•	M5
+•	Conditional Decision Trees
+Bayesian Algorithms
+•	Naive Bayes
+•	Gaussian Naive Bayes
+•	Multinomial Naive Bayes
+•	Averaged One-Dependence Estimators (AODE)
+•	Bayesian Belief Network (BBN)
+•	Bayesian Network (BN)
+Clustering Algorithms
+•	k-Means
+•	k-Medians
+•	Expectation Maximisation (EM)
+•	Hierarchical Clustering
+Association Rule Learning Algorithms
+•	Apriori algorithm
+•	Eclat algorithm
+Artificial Neural Network Algorithms
+•	Perceptron
+•	Multilayer Perceptrons (MLP)
+•	Back-Propagation
+•	Stochastic Gradient Descent
+•	Hopfield Network
+•	Radial Basis Function Network (RBFN)
+
+
+Deep Learning Algorithms
+•	Convolutional Neural Network (CNN)
+•	Recurrent Neural Networks (RNNs)
+•	Long Short-Term Memory Networks (LSTMs)
+•	Stacked Auto-Encoders
+•	Deep Boltzmann Machine (DBM)
+•	Deep Belief Networks (DBN)
+Dimensionality Reduction Algorithms
+•	Principal Component Analysis (PCA)
+•	Principal Component Regression (PCR)
+•	Partial Least Squares Regression (PLSR)
+•	Sammon Mapping
+•	Multidimensional Scaling (MDS)
+•	Projection Pursuit
+•	Linear Discriminant Analysis (LDA)
+•	Mixture Discriminant Analysis (MDA)
+•	Quadratic Discriminant Analysis (QDA)
+•	Flexible Discriminant Analysis (FDA)
+Ensemble Algorithms
+•	Boosting
+•	Bootstrapped Aggregation (Bagging)
+•	AdaBoost
+•	Weighted Average (Blending)
+•	Stacked Generalization (Stacking)
+•	Gradient Boosting Machines (GBM)
+•	Gradient Boosted Regression Trees (GBRT)
+•	Random Forest
+