Classification based on decision tree algorithm for machine learning
B Charbuty, A Abdulazeez - Journal of Applied Science and Technology …, 2021 - jastt.org
Decision tree classifiers are regarded to be a standout of the most well-known methods to
data classification representation of classifiers. Different researchers from various fields and …
data classification representation of classifiers. Different researchers from various fields and …
Diagnosis of monkeypox disease using transfer learning and binary advanced dipper throated optimization algorithm
The virus that causes monkeypox has been observed in Africa for several years, and it has
been linked to the development of skin lesions. Public panic and anxiety have resulted from …
been linked to the development of skin lesions. Public panic and anxiety have resulted from …
Predicting the travel mode choice with interpretable machine learning techniques: A comparative study
MT Kashifi, A Jamal, MS Kashefi… - Travel Behaviour and …, 2022 - Elsevier
Prediction of mode choice for travelers has been the subject of keen interest among
transportation planners. Traditionally, mode choice analysis is conducted by statistical …
transportation planners. Traditionally, mode choice analysis is conducted by statistical …
A systematic comparative evaluation of machine learning classifiers and discrete choice models for travel mode choice in the presence of response heterogeneity
Discrete choice models has been for decades the most used technique to model travel
mode choice, being the multinomial logit (MNL) the most popular model among them …
mode choice, being the multinomial logit (MNL) the most popular model among them …
Game theory applications in traffic management: A review of authority-based travel modelling
With the exponential growth in urbanization, urban traffic congestion has become a
challenging task with an adverse impact on the economic structure and ecosystem …
challenging task with an adverse impact on the economic structure and ecosystem …
[HTML][HTML] Choice modelling in the age of machine learning-discussion paper
Since its inception, the choice modelling field has been dominated by theory-driven
modelling approaches. Machine learning offers an alternative data-driven approach for …
modelling approaches. Machine learning offers an alternative data-driven approach for …
Enhancing discrete choice models with representation learning
In discrete choice modeling (DCM), model misspecifications may lead to limited
predictability and biased parameter estimates. In this paper, we propose a new approach for …
predictability and biased parameter estimates. In this paper, we propose a new approach for …
[HTML][HTML] Comparing urban form influences on travel distance, car ownership, and mode choice
Steady growth in global greenhouse gas emissions from transport is driven by growing
demand for car travel. A sizable body of research investigates influences of urban form on …
demand for car travel. A sizable body of research investigates influences of urban form on …
Monitoring the Industrial waste polluted stream-Integrated analytics and machine learning for water quality index assessment
Abstract The Water Quality Index (WQI) is a primary metric used to evaluate and categorize
surface water quality which plays a crucial role in the management of fresh water resources …
surface water quality which plays a crucial role in the management of fresh water resources …
[HTML][HTML] Comparing and contrasting choice model and machine learning techniques in the context of vehicle ownership decisions
In recent years, planners have started considering Machine Learning (ML) techniques as an
alternative to discrete choice models (CM). ML techniques are primarily data-driven and …
alternative to discrete choice models (CM). ML techniques are primarily data-driven and …