同时推断聚类类结构和批量校正的半监督和无监督贝叶斯混合模型。可用密度为多元正态和多元t。模型采样器用C++实现。该软件包旨在分析跨多个批次生成的低维数据。有关模型的详细信息，请参见[Coleman等人，2022]（https:doi.org 10.1101 2022.01.14.476352）。
Semi-supervised and unsupervised Bayesian mixture models that simultaneously infer the cluster class structure and a batch correction. Densities available are the multivariate normal and the multivariate t. The model sampler is implemented in C++. This package is aimed at analysis of low-dimensional data generated across several batches. See [Coleman et al., 2022](https: doi.org 10.1101 2022.01.14.476352) for details of the model. (2024-02-16, R, 0KB, 下载0次)
肝脏疾病的预测，。。。贝叶斯分类器随机森林决策树K-最近邻支持向量机人工神经网络...
Aim of this project is to build a best model to predict liver disease and use that model for human being to avoid risk of health, money and to give better health. In that i worked on near about 8 machine learning methods namely Logistic Regression Naive Bayes Classifier Random Forest Decision Tree K-Nearest Neighbors Support Vector Machine (2021-03-15, R, 4622KB, 下载0次)