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There are various methods that have come into existence for similarity calculation between two different objects of similar domain that can be feature vectors, such as kernels. Multiple kernel learning methods show considerable level of prediction accuracy as compared to single kernels in existing systems. This paper primarily focuses on binary classification problems in cheminformatics specifically...
There have been various measures and techniques which have currently been used in order to measure the similarity between graphs [1]. In this paper, molecules have been represented as graphs with atoms of the molecule being represented as nodes and bonds between atoms being represented as edges [2]. We will first see how various available similarity coefficients perform in order to measure the similarity...
Support Vector Machines (SVM's) are supervised learning algorithms which can be used for analyzing patterns and classifying data. This supervised algorithm is applicable for binary class as well as multiclass classification. The core idea is to build a hyperplane which can easily separate the training examples. For binary class, SVM constructs a hyper-plane which can easily separate d-dimensional...
Machine learning can play a very important role in various crucial applications like data mining and pattern recognition. Machine learning techniques have been widely used in drug discovery and development, particularly in the areas of chemo-informatics, bioinformatics and other types of pharmaceutical research. It has been demonstrated that they are suitable for large high dimensional data, and the...
Farmers in India have small land holdings and due to this, analyzing hyperspectral images becomes an issue. Due to a high probability of obstacles in small land holding areas, hyper spectral images will give less accuracy. So, the major concern will be to remove obstacles in the small land holdings by using an unsupervised segmentation method. The base data set used consists of hyperspectral images...
By collecting real time data on weather, soil and air quality, crop maturity, Precision agriculture (PA) has become an emerging topic in recent years. Management zone delineation is the major task in PA, which could help to discover the spatially contiguous zones of the field. This article studies the different data mining approaches for achieving management zone delineation with their advantages...
Drug discovery is a time-consuming and costly process. The data generated during various stages of the drug discovery is drastically increasing and it forces machine-learning scientist to implement more effective and fast methods for the utilization of data for reducing the cost and time. Molecular graphs are very expressive which allow faster implementation of the machine-learning algorithms. During...
For any successful launch of product, it should be properly reviewed. This is done by conducting a meeting in which various participants give their opinions, and depending upon those opinions decision is made. Firstly, it was given by Anvil tool, which was difficult to analyze. Also, commands such as propose, acknowledgement, negative response do not have a predefined notion which can differentiate...
In the paper we are showing a comparative study of some of the classification and the clustering algorithms so that we can find the alternatives for the datasets depending upon the requirement. These prediction systems can be used for the medical diagnosis as various algorithms in this paper have been categorized and simulation results shown. Prevalence informs the total case load at a given time...
In the paper we are showing a comparative study of some of the classification and the clustering algorithms so that we can find the alternatives for the datasets depending upon the requirement. These prediction systems can be used for the software fault prediction as various algorithms in this paper have been categorized and simulation results shown. Prevalence informs the total case load at a given...
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