পদ্ধতির তুলনা করুন

	সিদ্ধান্ত বৃক্ষ	আইসোলেশন ফরেস্ট
ক্ষেত্র	যন্ত্র শিখন	যন্ত্র শিখন
পরিবার	Machine learning	Machine learning
উদ্ভবের বছর	1984	2008
প্রবর্তক	Breiman, Friedman, Olshen & Stone	Liu, F.T., Ting, K.M. & Zhou, Z.-H.
ধরন	Recursive partitioning (if-then rules)	Unsupervised ensemble (random partitioning trees)
মৌলিক উৎস	Breiman, L., Friedman, J.H., Olshen, R.A. & Stone, C.J. (1984). Classification and Regression Trees. Wadsworth.	Liu, F.T., Ting, K.M. & Zhou, Z.-H. (2008). Isolation Forest. IEEE ICDM, 413–422.
অপর নাম	Karar Ağacı (Decision Tree), karar ağacı, classification tree, regression tree	Isolation Forest (Aykırı Değer Tespiti), iForest, isolation forest anomaly detection
সম্পর্কিত	5	5
সারসংক্ষেপ	A Decision Tree is an interpretable classification and regression method, formalised by Breiman, Friedman, Olshen and Stone in their 1984 CART framework, that partitions the data with hierarchical if-then rules. Each split sends observations down one branch or another until a prediction is read off the leaf.	Isolation Forest is an unsupervised machine-learning method for anomaly and outlier detection, introduced by Liu, Ting and Zhou in 2008, that isolates anomalies through random partitioning of the data. It works without any labelled anomaly data and scales to high-dimensional datasets.