Network-based piecewise linear regression for QSAR modelling
نویسندگان
چکیده
منابع مشابه
A Learning Algorithm for Piecewise Linear Regression
A new learning algorithm for solving piecewise linear regression problems is proposed. It is able to train a proper multilayer feedforward neural network so as to reconstruct a target function assuming a different linear behavior on each set of a polyhedral partition of the input domain. The proposed method combine local estimation, clustering in weight space, classification and regression in o...
متن کاملStepwise Linear Regression for Dimensionality Reduction in Neural Network Modelling
This work considers the applicability of applying the derivatives of stepwise linear regression modelling (specifically the p-values which indicate the importance of a variable to the modelling process) as a feature extraction technique. We utilise it in conjunction with several data sets of varying levels of complexity, and compare our results to other dimensionality reduction techniques such ...
متن کاملnetwork optimization with piecewise linear convex costs
the problem of finding the minimum cost multi-commodity flow in an undirected and completenetwork is studied when the link costs are piecewise linear and convex. the arc-path model and overflowmodel are presented to formulate the problem. the results suggest that the new overflow model outperformsthe classical arc-path model for this problem. the classical revised simplex, frank and wolf and a ...
متن کاملLinear Regression QSAR Models for Polo-Like Kinase-1 Inhibitors
A structurally diverse dataset of 530 polo-like kinase-1 (PLK1) inhibitors is compiled from the ChEMBL database and studied by means of a conformation-independent quantitative structure-activity relationship (QSAR) approach. A large number (26,761) of molecular descriptors are explored with the main intention of capturing the most relevant structural characteristics affecting the bioactivity. T...
متن کاملPiecewise Linear Regression for Massive Data through Dataspheres
We propose enhancing the tting of linear regression models to massive multidimensional data by partitioning the data using a DataSphere (proposed in our previous work) and tting piecewise linear regression models to each class in the representation. Nonlinear models typically involve several iterations through the data and require the knowledge of every data point. Linear regression models, on ...
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 Computer-Aided Molecular Design
سال: 2019
ISSN: 0920-654X,1573-4951
DOI: 10.1007/s10822-019-00228-6