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Support Vector Machines-Based Quantitative Structure−Property Relationship for the Prediction of Heat Capacity

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What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

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Estimation of Dependences Based on Empirical Data

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The Nature of Statistical Learning Theory

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Radial basis function network-based quantitative structure–property relationship for the prediction of Henry’s law constant

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Membership authentication in the dynamic group by face classification using SVM ensemble

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Hyperparameter design criteria for support vector classifiers

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Diagnosing Breast Cancer Based on Support Vector Machines

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Comparison of Support Vector Machine and Artificial Neural Network Systems for Drug/Nondrug Classification

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An Accurate QSPR Study of O−H Bond Dissociation Energy in Substituted Phenols Based on Support Vector Machines

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Study of the Quantitative Structure-Mobility Relationship of Carboxylic Acids in Capillary Electrophoresis Based on Support Vector Machines

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A Tutorial on Support Vector Machines for Pattern Recognition

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A tutorial on support vector regression

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Estimation of Dependences Based on Empirical Data.

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Genetic algorithms in search, optimization, and machine learning

What points at this work

Incoming claims: where this work appears in other papers’ reference lists and arguments.

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Prediction of liquid‐crystalline property using support vector machine classification

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Support Vector Machines‐Based Quantitative Structure—Property Relationship for the Prediction of Heat Capacity.

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Machine learning approaches for predicting compounds that interact with therapeutic and ADMET related proteins

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Quantitative Structure–Activity Relationships Study on the Ah Receptor Binding Affinities of Polybrominated Diphenyl Ethers Using a Support Vector Machine

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QSAR study on the Ah receptor-binding affinities of polyhalogenated dibenzo-p-dioxins using net atomic-charge descriptors and a radial basis neural network

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Considerations and recent advances in QSAR models for cytochrome P450-mediated drug metabolism prediction

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A New Group-Contribution Approach for Ideal Gas Heat Capacity, Critical Temperature and Normal Boiling Point

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QSAR Models for the Prediction of Binding Affinities to Human Serum Albumin Using the Heuristic Method and a Support Vector Machine

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One- to Four-Dimensional Kernels for Virtual Screening and the Prediction of Physical, Chemical, and Biological Properties

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Quantitative Structure–Property Relationship Prediction of Gas Heat Capacity for Organic Compounds

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A pyrrolidinium nitrate protic ionic liquid-based electrolyte for very low-temperature electrical double-layer capacitors

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Computational identification of organic porous molecular crystals

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Enhanced thermophysical property prediction with uncertainty quantification using group contribution-Gaussian process regression

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A novel approach to generate robust classification models to predict developmental toxicity from imbalanced datasets

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Machine‐learning predictions of caffeine co‐crystal formation accompanying experimental and molecular validations

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A Study on Factors Affecting the Reproducibility of a Chemical Tongue Analysis Responding to Amino Acids

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Thermal conductivity data acquisition using microfluidics and cheminformatics

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