Journal of Artificial Intelligence Research
SCOPUS (1993,1996-2025)SCIE-ISI
1076-9757
1943-5037
Mỹ
Cơ quản chủ quản: Morgan Kaufmann Publishers, Inc. , AI ACCESS FOUNDATION
Lĩnh vực:
Artificial Intelligence
Các bài báo tiêu biểu
SMOTE: Synthetic Minority Over-sampling Technique
Tập 16 - Trang 321-357
An approach to the construction of classifiers from imbalanced datasets is
described. A dataset is imbalanced if the classification categories are not
approximately equally represented. Often real-world data sets are predominately
composed of ``normal'' examples with only a small percentage of ``abnormal'' or
``interesting'' examples. It is also the case that the cost of misclassifying an
abnormal...
Reinforcement Learning: A Survey
Tập 4 - Trang 237-285
This paper surveys the field of reinforcement learning from a computer-science
perspective. It is written to be accessible to researchers familiar with machine
learning. Both the historical basis of the field and a broad selection of
current work are summarized. Reinforcement learning is the problem faced by an
agent that learns behavior through trial-and-error interactions with a dynamic
environm...
Popular Ensemble Methods: An Empirical Study
Tập 11 - Trang 169-198
An ensemble consists of a set of individually trained classifiers (such as
neural networks or decision trees) whose predictions are combined when
classifying novel instances. Previous research has shown that an ensemble is
often more accurate than any of the single classifiers in the ensemble. Bagging
(Breiman, 1996c) and Boosting (Freund & Shapire, 1996; Shapire, 1990) are two
relatively new but ...
Solving Multiclass Learning Problems via Error-Correcting Output Codes
Tập 2 - Trang 263-286
Multiclass learning problems involve finding a definitionfor an unknown function
f(x) whose range is a discrete setcontaining k > 2 values (i.e., k ``classes'').
Thedefinition is acquired by studying collections of training examples ofthe
form [x_i, f (x_i)]. Existing approaches tomulticlass learning problems include
direct application of multiclassalgorithms such as the decision-tree algorithms
C...
Semantic Similarity in a Taxonomy: An Information-Based Measure and its Application to Problems of Ambiguity in Natural Language
Tập 11 - Trang 95-130
This article presents a measure of semantic similarity in an IS-A taxonomy based
on the notion of shared information content. Experimental evaluation against a
benchmark set of human similarity judgments demonstrates that the measure
performs better than the traditional edge-counting approach. The article
presents algorithms that take advantage of taxonomic similarity in resolving
syntactic and se...
Improved Use of Continuous Attributes in C4.5
Tập 4 - Trang 77-90
A reported weakness of C4.5 in domains with continuous attributes is addressed
by modifying the formation and evaluation of tests on continuous attributes. An
MDL-inspired penalty is applied to such tests, eliminating some of them from
consideration and altering the relative desirability of all tests. Empirical
trials show that the modifications lead to smaller decision trees with higher
predictiv...
SMOTE for Learning from Imbalanced Data: Progress and Challenges, Marking the 15-year Anniversary
Tập 61 - Trang 863-905
The Synthetic Minority Oversampling Technique (SMOTE) preprocessing algorithm is
considered "de facto" standard in the framework of learning from imbalanced
data. This is due to its simplicity in the design of the procedure, as well as
its robustness when applied to different type of problems. Since its publication
in 2002, SMOTE has proven successful in a variety of applications from several
diff...
Improved Heterogeneous Distance Functions
Tập 6 - Trang 1-34
Instance-based learning techniques typically handle continuous and linear input
values well, but often do not handle nominal input attributes appropriately. The
Value Difference Metric (VDM) was designed to find reasonable distance values
between nominal attribute values, but it largely ignores continuous attributes,
requiring discretization to map continuous values into nominal values. This
paper...
A Multiagent Approach to Autonomous Intersection Management
Tập 31 - Trang 591-656
Artificial intelligence research is ushering in a new era of sophisticated,
mass-market transportation technology. While computers can already fly a
passenger jet better than a trained human pilot, people are still faced with the
dangerous yet tedious task of driving automobiles. Intelligent Transportation
Systems (ITS) is the field that focuses on integrating information technology
with vehicles ...
Active Learning with Statistical Models
Tập 4 - Trang 129-145
For many types of machine learning algorithms, one can compute the statistically
`optimal' way to select training data. In this paper, we review how optimal data
selection techniques have been used with feedforward neural networks. We then
show how the same principles may be used to select data for two alternative,
statistically-based learning architectures: mixtures of Gaussians and locally
weigh...