Analysis of AneuRisk65 data: $k$-mean alignment

Analysis of AneuRisk65 data: warped logistic discrimination∗

We analyze the AneuRisk65 curvature functions using a likelihoodbased warping method for sparsely sampled curves, and combine it with logistic regression in order to discriminate subjects with aneurysms at or after the terminal bifurcation of the internal carotid artery (the most life-threatening) from subjects with no aneurysms or aneurysms along the carotid artery (the less serious). Signific...

Comparative Analysis of Hybrid K-Mean Algorithms on Data Clustering

Data clustering is a process of organizing data into certain groups such that the objects in the one cluster are highly similar but dissimilar to the data objects in other clusters. K-means algorithm is one of the popular algorithms used for clustering but k-means algorithm have limitations like it is sensitive to noise ,outliers and also it does not provides global optimum results. To overcome...

k-equitable mean labeling

Clustering of Data Using K-Mean Algorithm

Clustering is associate automatic learning technique geared toward grouping a collection of objects into subsets or clusters. The goal is to form clusters that are coherent internally, however well completely different from one another. In plain words, objects within the same cluster ought to be as similar as potential, whereas objects in one cluster ought to be as dissimilar as potential from ...

Identification of BKCa channel openers by molecular field alignment and patent data-driven analysis

In this work, we present the first comprehensive molecular field analysis of patent structures on how the chemical structure of drugs impacts the biological binding. This task was formulated as searching for drug structures to reveal shared effects of substitutions across a common scaffold and the chemical features that may be responsible. We used the SureChEMBL patent database, which prov...