JPlogP: an improved logP predictor trained using predicted data
نویسندگان
چکیده
منابع مشابه
Improved Meta Analysis Using Predicted Relative Risk
This paper proposes a new method of improved meta analysis to combine relative risk for both homogeneous and heterogeneous set of studies. The standard meta analyses don’t give any conclusive result when the effects of heterogenous studies are combined. The proposed improved meta analysis uses the predicted relative risk, and chi-square test to check the heterogeneity of the effects. Confidence...
متن کاملAn improved opposition-based Crow Search Algorithm for Data Clustering
Data clustering is an ideal way of working with a huge amount of data and looking for a structure in the dataset. In other words, clustering is the classification of the same data; the similarity among the data in a cluster is maximum and the similarity among the data in the different clusters is minimal. The innovation of this paper is a clustering method based on the Crow Search Algorithm (CS...
متن کاملAn improved GMM-based voice quality predictor
A voice quality prediction method based on Gaussian mixture models (GMMs) is improved by constructing a feature selection algorithm to provide the best GMMbased prediction quality. The proposed sequential selection algorithm performs N -survivor search, allowing for trading between design complexity and performance. Simulation shows that predictors designed using the proposed algorithm outperfo...
متن کاملImproved classification of medical data using abductive network committees trained on different feature subsets
This paper demonstrates the use of abductive network classifier committees trained on different features for improving classification accuracy in medical diagnosis. In an earlier publication, committee members were trained on different subsets of the training set to ensure enough diversity for improved committee performance. In situations characterized by high data dimensionality, i.e. a large ...
متن کاملData Pre-processing for a Neural Network Trained by an Improved Particle Swarm Optimization Algorithm
This paper proposes an improved version of particle swarm optimization (PSO) algorithm for the training of a neural network (NN). An architecture for the NN trained by PSO (standard PSO, improved PSO) is also introduced. This architecture has a data preprocessing mechanism which consists of a normalization module and a data-shuffling module. Experimental results showed that the NN trained by im...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Journal of Cheminformatics
سال: 2018
ISSN: 1758-2946
DOI: 10.1186/s13321-018-0316-5