On the Power of Ensemble: Supervised and Unsupervised Methods
... Do not prefer one base model over the other, just average them ...
... Do not prefer one base model over the other, just average them ...
Which Space Partitioning Tree to Use for Search?
... Nearest-neighbor search is ubiquitous in computer science. Several techniques exist for nearestneighbor search, but most algorithms can be categorized into two following groups based on the indexing scheme used – (1) search with hierarchical tree indices, or (2) search with hash-based indices. Altho ...
... Nearest-neighbor search is ubiquitous in computer science. Several techniques exist for nearestneighbor search, but most algorithms can be categorized into two following groups based on the indexing scheme used – (1) search with hierarchical tree indices, or (2) search with hash-based indices. Altho ...
Mining Association Rules Based on Certainty
... k-length item sets. After that, it scans the transaction database to determine frequent item sets among the candidates. Apriori, while is historically significant, suffers from a number of inefficiencies or trade-offs, which have given rise to other algorithms. Candidate set generates large numbers ...
... k-length item sets. After that, it scans the transaction database to determine frequent item sets among the candidates. Apriori, while is historically significant, suffers from a number of inefficiencies or trade-offs, which have given rise to other algorithms. Candidate set generates large numbers ...
A New Intrusion Detection System using Support Vector Machines and Hierarchical Clustering
... attacks [18, 26, 27]. Host-based attacks target a machine and try to gain access to privileged services or resources on that machine. Host-based detection usually uses routines that obtain system call data from an audit-process which tracks all system calls made on behalf of each user. Network-based ...
... attacks [18, 26, 27]. Host-based attacks target a machine and try to gain access to privileged services or resources on that machine. Host-based detection usually uses routines that obtain system call data from an audit-process which tracks all system calls made on behalf of each user. Network-based ...
Survey of Clustering Algorithms (PDF Available)
... from the used algorithms. These assessments should be objective and have no preferences to any algorithm. Also, they should be useful for answering questions like how many clusters are hidden in the data, whether the clusters obtained are meaningful or just an artifact of the algorithms, or why we c ...
... from the used algorithms. These assessments should be objective and have no preferences to any algorithm. Also, they should be useful for answering questions like how many clusters are hidden in the data, whether the clusters obtained are meaningful or just an artifact of the algorithms, or why we c ...
Nearest-neighbor chain algorithm
In the theory of cluster analysis, the nearest-neighbor chain algorithm is a method that can be used to perform several types of agglomerative hierarchical clustering, using an amount of memory that is linear in the number of points to be clustered and an amount of time linear in the number of distinct distances between pairs of points. The main idea of the algorithm is to find pairs of clusters to merge by following paths in the nearest neighbor graph of the clusters until the paths terminate in pairs of mutual nearest neighbors. The algorithm was developed and implemented in 1982 by J. P. Benzécri and J. Juan, based on earlier methods that constructed hierarchical clusterings using mutual nearest neighbor pairs without taking advantage of nearest neighbor chains.