With the development of urbanization, hourly PM2.5 concentration in air is constantly changing. In order to improve accuracy prediction, a prediction model based on Classification and Regression Tree (CART) Broad Learning System (BLS) was constructed. Firstly, CART algorithm used segment dataset hierarchical way obtain subset with similar characteristics. Secondly, BLS trained by using data eac...

This paper is devoted to the problem of learning to predict ordinal (i.e., ordered discrete) classes using classification and regression trees. We start with S-CART, a tree induction algorithm, and study various ways of transforming it into a learner for ordinal classification tasks. These algorithm variants are compared on a number of benchmark data sets to verify the relative strengths and we...

Forest types mapping is one of the most necessary elements in forest management and Silviculture treatments. Traditional methods such as field surveys are time-consuming and cost-intensive. Improving satellite data sources and classification methods offer new opportunities for obtaining more accurate forest biophysical maps. This research compares performance of three non-parametric and tree-ba...

The main goal of this paper is to present and evaluate the possibility of using the methods and tools of Artificial Intelligence and Data Mining to analyze marketing data needed to support decision-making in the process of market segmentation. This paper describes the application of Kohonen’s Neural Networks and Classification Trees (including tools such as CART-Classification and Regression Tr...

BACKGROUND/AIM Assessing prognosis for acetaminophen-induced acute liver failure (APAP-ALF) patients often presents significant challenges. King's College (KCC) has been validated on hospital admission, but little has been published on later phases of illness. We aimed to improve determinations of prognosis both at the time of and following admission for APAP-ALF using Classification and Regres...

We evaluated the predictive power of two classification techniques, one parametric !/ discriminant function analysis (DFA) and the other non-parametric !/ classification and regression tree analysis (CART), in order to provide a non-subjective quantitative method of determining age class in Vancouver Island marmots (Marmota vancouverensis ) and hoary marmots (Marmota caligata ). For both techni...

â  using of prediction models is one of the methods of financial performance prediction. financial ratios are employed as predictive variable in prediction models. the main purpose of this study is to compare the incremental information content of accrual and cash ratios for prediction and evaluation of the financial performance of business entities by data mining models. in align with research...

Human population growth and land use cover (LULC) change have always developed side by side. Considering selection of a good Machine Learning (ML) classifier algorithm is needed considering the high estimation LULC maps based on remote sensing. This study aims to produce classification Landsat-8 Sentinel-2 images comparing accuracy performance three ML algorithms, namely: Classification Regress...

Balance-sheet data offer a potentially large number of candidate predictors of corporate financial failure. In this paper we provide a novel predictor selection procedure based on non-parametric regression and classification tree method (CART) and test its performance within a standard logit model. We show that a simple logit model with dummy variables created in accordance with the nodes of es...