Feature-Weighting and Clustering Random Forest

[1]  YAN LI,et al.  Using a Variable Weighting k-Means Method to Build a Decision Cluster Classification Model , 2012, Int. J. Pattern Recognit. Artif. Intell..

[2]  Ian H. Witten,et al.  The WEKA data mining software: an update , 2009, SKDD.

[3]  Alberto Maria Segre,et al.  Programs for Machine Learning , 1994 .

[4]  Tin Kam Ho,et al.  The Random Subspace Method for Constructing Decision Forests , 1998, IEEE Trans. Pattern Anal. Mach. Intell..

[5]  Tsuyoshi Murata,et al.  {m , 1934, ACML.

[6]  Juana Canul-Reich,et al.  Construction of Near-Optimal Axis-Parallel Decision Trees Using a Differential-Evolution-Based Approach , 2018, IEEE Access.

[7]  Yoav Freund,et al.  A decision-theoretic generalization of on-line learning and an application to boosting , 1995, EuroCOLT.

[8]  Dipti P. Rana,et al.  Random Forest Classifier Approach for Imbalanced Big Data Classification for Smart City Application Domains , 2018 .

[9]  C. J. Price,et al.  HHCART: An oblique decision tree , 2015, Comput. Stat. Data Anal..

[10]  Leo Breiman,et al.  Bagging Predictors , 1996, Machine Learning.

[11]  Shuhei Kimura,et al.  Inference of genetic networks using random forests: Assigning different weights for gene expression data , 2019, J. Bioinform. Comput. Biol..

[12]  Huijuan Lu,et al.  Kernel principal component analysis combining rotation forest method for linearly inseparable data , 2018, Cognitive Systems Research.

[13]  Leo Breiman,et al.  Random Forests , 2001, Machine Learning.

[14]  Wray L. Buntine,et al.  Learning classification trees , 1992 .

[15]  Farid García,et al.  Fisher's decision tree , 2013, Expert Syst. Appl..

[16]  Igor Kononenko,et al.  Estimating Attributes: Analysis and Extensions of RELIEF , 1994, ECML.

[17]  Zenon A. Sosnowski,et al.  Knowledge aggregation in decision-making process with C-fuzzy random forest using OWA operators , 2019, Soft Comput..

[18]  Ullrich Köthe,et al.  On Oblique Random Forests , 2011, ECML/PKDD.

[19]  Witold Pedrycz,et al.  C-fuzzy decision trees , 2005, IEEE Transactions on Systems, Man, and Cybernetics, Part C (Applications and Reviews).

[20]  R. Bucy,et al.  Decision tree design by simulated annealing , 1993 .

[21]  Serge N. Demidenko,et al.  Multivariate alternating decision trees , 2016, Pattern Recognit..

[22]  Joshua Zhexue Huang,et al.  Extensions to the k-Means Algorithm for Clustering Large Data Sets with Categorical Values , 1998, Data Mining and Knowledge Discovery.

[23]  Abdessalam Elhabbash,et al.  Enhanced k-means Clustering Algorithm , 2010 .

[24]  Le Zhang,et al.  An ensemble of decision trees with random vector functional link networks for multi-class classification , 2017, Appl. Soft Comput..

[25]  Simon Kasif,et al.  A System for Induction of Oblique Decision Trees , 1994, J. Artif. Intell. Res..

[26]  Mohsen Naderpour,et al.  Credit risk prediction in an imbalanced social lending environment , 2018, Int. J. Comput. Intell. Syst..

[27]  G. Fitzgerald,et al.  'I. , 2019, Australian journal of primary health.

[28]  Larry A. Rendell,et al.  A Practical Approach to Feature Selection , 1992, ML.

[29]  C. Sitthi-amorn,et al.  Bias , 1993, The Lancet.

[30]  Juan José Rodríguez Diez,et al.  Rotation Forest: A New Classifier Ensemble Method , 2006, IEEE Transactions on Pattern Analysis and Machine Intelligence.