JSTOR Daily

Classifiers of Support Vector Machine Type with l₁ Complexity Regularization

We study the binary classification problem with hinge loss. We consider classifiers that are linear combinations of base functions. Instead of an l₂ penalty, which is used by the support vector ...
ascopubs.org

Immunomarker combined with clinical features to support vector machines classifier for prediction of gastric cancer survival and adjuvant chemotherapeutic benefits.

Role of infiltrating CD8 lymphocytes, microsatellite instability and h. pylori level in gastric cancer. Response to immune checkpoint inhibitors in recurrent/metastatic esophageal squamous cell ...
ascopubs.org

Three Immunomarker Support Vector Machines–Based Prognostic Classifiers for Stage IB Non–Small-Cell Lung Cancer

Phase I Study of Lapatinib in Combination With Chemoradiation in Patients With Locally Advanced Squamous Cell Carcinoma of the Head and Neck zWhen we use a single clinicopathologic feature or ...
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Breakthrough in MAX phases: Machine learning unlocks new materials

Data on all known stable MAX phases were collected from experimental literature, and non-existent MAX phases were identified using existing first-principles results. Models such as the Random Forest ...
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Forecasting natural gas price trends using random forest and support vector machine classifiers

Price forecasting using statistical modeling methods and data mining has been a topic of great interest among data scientists around the world. In this paper, different machine learning approaches are ...
JSTOR Daily

Coupling a Markov Chain and Support Vector Machine for At-Site Downscaling of Daily Precipitation

Statistical downscaling is useful for managing scale and resolution problems in outputs from global climate models (GCMs) for climate change impact studies. To improve downscaling of precipitation ...