[HTML][HTML] Basic tenets of classification algorithms K-nearest-neighbor, support vector machine, random forest and neural network: A review
In this paper, sixty-eight research articles published between 2000 and 2017 as well as
textbooks which employed four classification algorithms: K-Nearest-Neighbor (KNN) …
textbooks which employed four classification algorithms: K-Nearest-Neighbor (KNN) …
Applications of machine learning to BIM: A systematic literature review
Abstract As Building Information Modeling (BIM) workflows are becoming very relevant for
the different stages of the project's lifecycle, more data is produced and managed across it …
the different stages of the project's lifecycle, more data is produced and managed across it …
A comparative analysis of logistic regression, random forest and KNN models for the text classification
In the current generation, a huge amount of textual documents are generated and there is an
urgent need to organize them in a proper structure so that classification can be performed …
urgent need to organize them in a proper structure so that classification can be performed …
Machine-learning phase prediction of high-entropy alloys
High-entropy alloys (HEAs) have been receiving intensive attention due to their unusual
properties that largely depend on the selection among three phases: solid solution (SS) …
properties that largely depend on the selection among three phases: solid solution (SS) …
Comparative study on KNN and SVM based weather classification models for day ahead short term solar PV power forecasting
Accurate solar photovoltaic (PV) power forecasting is an essential tool for mitigating the
negative effects caused by the uncertainty of PV output power in systems with high …
negative effects caused by the uncertainty of PV output power in systems with high …
A novel active learning method using SVM for text classification
Support vector machines (SVMs) are a popular class of supervised learning algorithms, and
are particularly applicable to large and high-dimensional classification problems. Like most …
are particularly applicable to large and high-dimensional classification problems. Like most …
An SVM-based solution for fault detection in wind turbines
Research into fault diagnosis in machines with a wide range of variable loads and speeds,
such as wind turbines, is of great industrial interest. Analysis of the power signals emitted by …
such as wind turbines, is of great industrial interest. Analysis of the power signals emitted by …
[HTML][HTML] A comprehensive survey on load forecasting hybrid models: Navigating the Futuristic demand response patterns through experts and intelligent systems
Load forecasting is a crucial task, which is carried out by utility companies for sake of power
grids' successful planning, optimized operation and control, enhanced performance, and …
grids' successful planning, optimized operation and control, enhanced performance, and …
[HTML][HTML] Toward an enhanced Arabic text classification using cosine similarity and Latent Semantic Indexing
FS Al-Anzi, D AbuZeina - Journal of King Saud University-Computer and …, 2017 - Elsevier
Cosine similarity is one of the most popular distance measures in text classification
problems. In this paper, we used this important measure to investigate the performance of …
problems. In this paper, we used this important measure to investigate the performance of …
A comparative study of the svm and k-nn machine learning algorithms for the diagnosis of respiratory pathologies using pulmonary acoustic signals
R Palaniappan, K Sundaraj, S Sundaraj - BMC bioinformatics, 2014 - Springer
Background Pulmonary acoustic parameters extracted from recorded respiratory sounds
provide valuable information for the detection of respiratory pathologies. The automated …
provide valuable information for the detection of respiratory pathologies. The automated …