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\node [root] {Algorithm}
[grow=right]
child [sibling distance=4.0cm] { node{Clustering}
child { node {k-Means}}
child { node {k-Medians}}
child { node {Expectation Maximisation (EM)}}
child { node {Hierarchical Clustering}}
}
child [sibling distance=4.5cm] { node {Bayesian}
child { node {Naive Bayes}}
child { node {Gaussian Naive Bayes}}
child { node {Multinomial Naive Bayes}}
child { node {Averaged One-Depen. Esti. (AODE)}}
child { node {Bayesian Belief Network (BBN)}}
child { node {Bayesian Network (BN)}}
}
child [sibling distance=0.5cm] { node {Decision Tree}
child { node {Classification and Regression Tree (CART)}}
child { node {Iterative Dichotomiser 3 (ID3)}}
child { node {C4.5 and C5.0}}
child { node {Chi-squared Auto.Inte. Det. (CHAID)}}
child { node {Decision Stump}}
child { node {M5}}
child { node {Conditional Decision Trees}}
}
child [sibling distance=5.5cm]{ node {Dimesionality Reduction}
child { node {[Principal Component Analysis (PCA)}}
child { node {Principal Component Regression (PCR)}}
child { node {Partial Least Squares Regression\\(PLSR)}}
child { node {Sammon Mapping}}
child { node {Multidimensional Scaling (MDS)}}
child { node {Projection Pursuit}}
child { node {Linear Discriminant Analysis (LDA)}}
child { node {Mixture Discriminant Analysis (MDA)}}
child { node {Quadratic Discriminant Analysis (QDA)}}
child { node {Flexible Discriminant Analysis (FDA)}}
}
child [sibling distance=5.cm] { node {Regularisation}
child { node {Ridge Regression}}
child { node {Least Abs. Shr. and Sel. Ope. (LASSO)}}
child { node {Elastic Net}}
child { node {Least-Angle Regression (LARS)}}
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\node [root]{Algorithm}
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child [sibling distance=3.1cm]{ node{Deep Learning}
child { node {Deep Boltzmann Machine (DBM)}}
child { node {Deep Belief Network (DBN)}}
child { node {Convolutional Neural Network (CNN)}}
child { node {Stacked Auto-Encoders}}
}
child [sibling distance=2.8cm]{ node {Ensamble}
child { node {Boosting}}
child { node {Bootstrapped Aggregation (Bagging)}}
child { node {AdaBoost}}
child { node {Stacked Generalization (blending)}}
child { node {Gradient Boosting Machines (GBM)}}
child { node {Gradient Boosted Regr. Trees (GBRT)}}
child { node {Random Forest}}
}
child { node{Neural Networks}
child { node {Perceptron}}
child { node {Back-Propagation}}
child { node {Hopfield Network}}
child { node {Radial Basis Function Net. (RBFN)}}
}
child[sibling distance=3.9cm] { node {Insatnce Based}
child { node {k-Nearest Neighbour(KNN)}}
child { node {Learning vector quantization(LVQ)}}
child { node {self-organised map}}
child { node {Locally Weighted Learning(LWL)}}
}
child[sibling distance=3.2cm] { node {Rule system}
child { node {Cubist}}
child { node {One Rule (OneR)}}
child { node {Zero Rule (ZeroR)}}
child { node {Rep.Inc.Pr2pro. Err. Red. (RIPPER)}}
}
child [sibling distance=3.3cm]{ node {Regression}
child { node {Linear}}
child { node {Ordinary Least Squares}}
child { node {Logistic}}
child { node {Stepwise}}
child { node {Locally Esti.Scatt. Smoo.(LOESS)}}
child { node {Multi. Ada. Reg.Splines (MARS)}}
};
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\end{document}