Results 71 to 80 of about 1,054,775 (163)
A comparative evaluation of deep and shallow approaches to the automatic detection of common grammatical errors [PDF]
, 2007 This paper compares a deep and a shallow processing approach to the problem of classifying a sentence as grammatically wellformed or ill-formed. The deep processing approach uses the XLE LFG parser and English grammar: two versions are presented, one ...
Foster, Jennifer +2 more
core
, 2020 Decision tree algorithms have been among the most popular algorithms for interpretable (transparent) machine learning since the early 1980's. The problem that has plagued decision tree algorithms since their inception is their lack of optimality, or lack
Hu, Xiyang +2 more
core
Verifiable Reinforcement Learning via Policy Extraction
, 2019 While deep reinforcement learning has successfully solved many challenging control tasks, its real-world applicability has been limited by the inability to ensure the safety of learned policies. We propose an approach to verifiable reinforcement learning
Bastani, Osbert +2 more
core
Prediction of Frost Occurrences Using Statistical Modeling Approaches
Advances in Meteorology, 2016 We developed the frost prediction models in spring in Korea using logistic regression and decision tree techniques. Hit Rate (HR), Probability of Detection (POD), and False Alarm Rate (FAR) from both models were calculated and compared.
Hyojin Lee +3 more
doaj +1 more source
Attribute Selection Based on Constraint Gain and Depth Optimal for a Decision Tree
Entropy, 2019 Uncertainty evaluation based on statistical probabilistic information entropy is a commonly used mechanism for a heuristic method construction of decision tree learning.
Huaining Sun, Xuegang Hu, Yuhong Zhang
doaj +1 more source
Penggunaan Decision Tree Dengan ID3 Algorithm Untuk Mengenali Dokumen Beraksara Jawa [PDF]
, 2015 This thesis\u27 goal is to let computer recognize Javanese letters. Before a computer is able to recognize Javanese letters, segmentation and feature extraction process is needed. After the features of Java letters that have been segmented obtained, then
Adipranata, R. (Rudy) +2 more
core
Improving Land Use/Land Cover Classification by Integrating Pixel Unmixing and Decision Tree Methods
Remote Sensing, 2017 Decision tree classification is one of the most efficient methods for obtaining land use/land cover (LULC) information from remotely sensed imageries. However, traditional decision tree classification methods cannot effectively eliminate the influence of
Chao Yang +5 more
doaj +1 more source
ANALYZING BIG DATA WITH DECISION TREES [PDF]
, 2014 ANALYZING BIG DATA WITH DECISION ...
Leong, Lok Kei
core +1 more source
Simplifying decision trees [PDF]
International Journal of Man-Machine Studies, 1987 Many systems have been developed for constructing decision trees from collections of examples. Although the decision trees generated by these methods are accurate and efficient, they often suffer the disadvantage of excessive complexity and are therefore incomprehensible to experts.
openaire +2 more sources
Optimization of decision trees using modified African buffalo algorithm
Journal of King Saud University: Computer and Information Sciences, 2022 Decision tree induction is a simple, however powerful learning and classification tool to discover knowledge from the database. The volume of data in databases is growing to quite large sizes, both in the number of attributes and instances.
Archana R. Panhalkar, Dharmpal D. Doye
doaj