ABSTRACT: Variable selection using penalized estimation methods in quantile regression models is an important step in screening for relevant covariates. In this paper, we present a one-step estimation ...

Kernel ridge regression (KRR) is a regression technique for predicting a single numeric value and can deliver high accuracy for complex, non-linear data. KRR combines a kernel function (most commonly ...

Background: Prognostic heterogeneity in stage II/III colorectal cancer (CRC) challenges clinical management, yet effective prognostic stratification is still lacking. To address this, we developed a ...

Background: Intratumor heterogeneity (ITH), a critical driver of tumor evolution and immune evasion, remains inadequately characterized at the transcriptomic level in colorectal cancer (CRC), and its ...

Abstract: Fuzzy classification models are important for handling uncertainty and heterogeneity in high-dimensional data. Although recent fuzzy logistic regression approaches have demonstrated ...

Traffic incidents significantly disrupt freeway operations, causing delays, congestion, fuel waste, and economic losses. Effective incident management requires not only rapid detection and clearance ...

Implement Logistic Regression in Python from Scratch ! In this video, we will implement Logistic Regression in Python from Scratch. We will not use any build in models, but we will understand the code ...

We already know that Ted Lasso season 4 is happening, and waiting for it to arrive is the hardest part. With production underway, Jason Sudeikis will return to Richmond in full Ted mode, and fans have ...