Operating profit hit a record high. Operating cash flow is also robust. Return on equity (ROE) has also improved ...

In the operation of X (formerly Twitter), operators who rely on subjective sense or vague conventional wisdom to determine "what kind of posts will grow" are, without exception, structurally weeded ...

Check the paper on ArXiv: FastBDT: A speed-optimized and cache-friendly implementation of stochastic gradient-boosted decision trees for multivariate classification Stochastic gradient-boosted ...

Finding relationships among data is an important skill for any business professional. Understanding cause-and-effect relationships can be the critical factor when it comes to wasted time, lost profits ...

Abstract: Quantum neural networks (QNNs) have shown remarkable potential due to their capability of representing complex functions within exponentially large Hilbert spaces. However, their application ...

This repository is for downscaling physical fields using multivariate linear regression. Here the model is applied to downscale significant wave height (SWH) in the Black Sea using low-resolution data ...

Assessing multivariate normality is a fundamental prerequisite in many statistical analyses, including multivariate regression, principal component analysis and discriminant analysis. A broad spectrum ...

多元自适应回归样条 多元自适应回归样条(Multivariate Adaptive Regression Splines,MARS)是由美国的统计学家Jerome Friedman于1991年提出的一种数据分析方法。 该方法以样条函数的张量积作为基函数,分为前向 ...

本内容遵循CC 4.0 BY-SA版权协议 练习1还包括一个房屋价格数据集，其中有2个变量（房子的大小，卧室的数量）和目标（房子的价格）。 我们使用我们已经应用的技术来分析数据集。 初始化一些 ...

Abstract: The log-binomial regression model is an essential tool for performing relative risk regression to analyze binary outcomes. The Hotelling T2 Control Chart is an effective multivariate process ...

The analysis of chemical data has undergone a profound transformation, from early basic statistical methods to the modern era of machine learning (ML) and artificial intelligence (AI). This ...