A large community of dedicated R users and programmers provides an excellent source of R code, functions, and data sets. R is also becoming adopted into commercial tools such as Oracle Database. Your investment in learning R is sure to pay off in the long term as R continues to grow ...
machine learning and predictive modeling in R, you can set yourself apart in your field and propel your career to new heights.Course Highlights:Thoroughly grasp the fundamentals of Machine Learning, Cluster Analysis, and Prediction Models, moving seamlessly from theory to practice.Apply supervised mach...
The caret package, short for classification and regression training, contains numerous tools for developing predictive models using the rich set of models available in R. The package focuses on simplifying model training and tuning across a wide variety of modeling techniques. It also includes methods...
you’ll learn fast effective ways to build powerful models using R. It contains over 90 of the most successful models used for learning from data; with step by step instructions on how to build them easily and quickly. • LEARN FASTER: 92 Applied Predictive Modeling Techniques in R offers...
Predictive Modeling of Urban Air Pollution Using Machine Learning and Unmanned Aerial Vehicle Platforms 来自 Springer 喜欢 0 阅读量: 1 作者: MM Zer 摘要: Air pollution poses a significant threat to human health on a global scale, with prolonged exposure to elevated ozone levels being particularly ...
能将实际问题转化成predictive modeling,并能使用RStudio 来完成基本的R packages 和command 能将相关数据和分析联系起来,使用数据和信息来初步建模 数据可视化-data visualization 能处理不同类型数据,和可视化挖掘数据 检测数据质量,处理数据存在的问题,从regulatory 和 ethic的角度来检查问题。
Stein, R. R. et al. Ecological modeling from time-series inference: insight into dynamics and stability of intestinal microbiota. PLoS Comput. Biol. 9, e1003388 (2013). PubMed PubMed Central Google Scholar Mannan, A. A. et al. Integrating kinetic model of E. coli with genome scale me...
The ACT-R computational modeling architecture has demonstrated the ability to model both recency and frequency effects in memory with much success (e.g. Anderon & Lebiere, 1998); and through the incorporation of new decay parameters at each data point, has also been shown to capture the spaci...
Modeling Interaction I. Scott MacKenzie, in Human-computer Interaction, 2013 7.2 Predictive models A predictive model is an equation. The equation predicts the outcome of a variable based on the value of one or more other variables (predictors). The outcome variable is a dependent variable, typic...
Among these, network-constrained sparse regression model is of particular interest due to its ability to utilize the prior graph/network structure in the omics data. Despite its potential usefulness for omics data analysis, no efficient R implementation is publicly available. Here we present an R ...