Sampling scheme-based classification rule mining method using decision tree in big data environment

Jin, Chi; Li, Fachao; Ma, Shijie; Wang, Ying

doi:10.1016/j.knosys.2022.108522

Cited by 25 publications

(14 citation statements)

References 38 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…[44] in the 1960s. Research has proven that DTs are easy to understand and quick to learn and classify [45]. For this, it remains a fundamental and privileged tool to obtain classification rules [46].…”

Section: Support Vector Machine Hyperparameter Tuningmentioning

confidence: 99%

Analysis of the severity of transport vehicle accidents by a comparative study of machine learning models

2023

IJATEE

View full text Add to dashboard Cite

Canada experiences an annual average of 1,700 road accident fatalities, along with countless injuries. Similarly, Australia witnesses over 1,000 fatalities and numerous serious injuries annually. The United States (U.S.), with over 38,000 collision-related deaths in 2020 and millions of dollars in property damage, ranks among the countries with the highest rates of road accidents. Given these alarming statistics, several countries, including Canada [2], Australia [3], and the U.S. [4], have been actively striving to develop innovative systems that can effectively prevent accidents.Effectively addressing the gravity of road crashes entails tackling several challenges. It is crucial to thoroughly consider factors such as the count of fatalities, injuries, and property losses to determine

show abstract

Section: Support Vector Machine Hyperparameter Tuningmentioning

confidence: 99%

Analysis of the severity of transport vehicle accidents by a comparative study of machine learning models

2023

IJATEE

View full text Add to dashboard Cite

show abstract

“…Decision tree [ 18 , 19 ] is a kind of inductive learning, and its structure is shown in Figure 4 . The generation of decision tree is a recursive process.…”

Section: Framework Of Platformmentioning

confidence: 99%

Design and Implementation of 3D Animation Data Processing Development Platform Based on Artificial Intelligence

Gao

2022

Computational Intelligence and Neuroscience

View full text Add to dashboard Cite

Based on the whole process of computer-aided technology, a 3D animation data processing development platform based on artificial intelligence is designed and implemented. A random forest model for animation data processing and development is designed to mine the experience that can guide animation generation from the accumulated animation data. Based on the design goal and implementation principle of animation data processing and development platform, the attributes and categories of random forest model are abstracted. After standardizing a large number of historical data, the training sample set is obtained, and the random forest model is obtained after training. The parameters of the random forest model are continuously optimized by experiments, so that the learning model can better guide the dynamic animation data processing and development platform to generate animation to the satisfaction of users. The designed three-dimensional animation data processing and development platform interacts with the animation generation module, users, and system administrators. It can continuously receive the sample data of the animation generation module, automatically expand the number of training samples, analyze the status of the sample database, and put forward suggestions to the system administrator to update the learning model, so as to realize the initiative of learning. The experimental results show that the designed 3D animation data processing and development platform is effective and feasible.

show abstract

“…Para su diseño se va a tener en consideración que los eventos estén ordenados cronológicamente, partiendo desde la izquierda hacia la derecha [17], como se observa en la Fig. 1.…”

Section: áRbol De Decisiónunclassified

Scenario analysis applied to mining for decision making and risk analysis

Chung¹,

Arévalo-Aranda²,

Retamozo³

et al. 2022

Proceedings of the 2nd LACCEI International Multiconference on Entrepreneurship, Innovation and Regional Development (LEIRD 202

View full text Add to dashboard Cite

The objective of this research was to analyze scenarios through decision making and risk analysis, which was applied in the construction of a cruise ship in the Atlantis project. The methodology that was used is quantitative based on event information, which through a graphical representation facilitated the understanding and interpretation of the decision tree, in addition, statistical methods were applied for risk analysis, it should be noted that in order to obtain data was considered that of other studies. The results obtained from the decision tree were that the first alternative that was proposed had a NPV of $3,970, the second of $3,405 and regarding the risk analysis, the coefficient of variation of the first option is 57% and the second 60%. Therefore, after having made the graphical representation and verified the risk, it is concluded that, for the construction of the cruiser, option 1 has the most viable decision regarding the path traced in the graph, the highest NPV and the lowest risk.

show abstract

Sampling scheme-based classification rule mining method using decision tree in big data environment

Cited by 25 publications

References 38 publications

Analysis of the severity of transport vehicle accidents by a comparative study of machine learning models

Analysis of the severity of transport vehicle accidents by a comparative study of machine learning models

Design and Implementation of 3D Animation Data Processing Development Platform Based on Artificial Intelligence

Scenario analysis applied to mining for decision making and risk analysis

Contact Info

Product

Resources

About