Types of machine learning algorithms. by Md. Merajul Islam (12646837)

“…Thus, the objectives of this study are to develop an appropriate model for predicting the risk of undernutrition and identify its influencing predictors among under-five children in Bangladesh using explainable machine learning algorithms.…”

ML algorithms in cyber security. by Abdullah Asım Yılmaz (20715311)

Statistics of the predictive performance indicators of four different competitor algorithms. by Jin Wang (29560)

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Ranking of ML algorithms. by Yasemin Ayaz Atalan (21989402)

“…For this purpose, well-known Machine Learning (ML) algorithms such as Random Forest (RF), Adaptive Boosting (AB), and Gradient Boosting (GB) were utilized. …”

DataSheet1_Study on risk factors of impaired fasting glucose and development of a prediction model based on Extreme Gradient Boosting algorithm.docx by Qiyuan Cui (19729288)

“…Objective<p>The aim of this study was to develop and validate a machine learning-based model to predict the development of impaired fasting glucose (IFG) in middle-aged and older elderly people over a 5-year period using data from a cohort study.…”

The overview of the ML algorithms’ flowchart. by Yasemin Ayaz Atalan (21989402)

“…For this purpose, well-known Machine Learning (ML) algorithms such as Random Forest (RF), Adaptive Boosting (AB), and Gradient Boosting (GB) were utilized. …”

Algorithmic experimental parameter design. by Chuanxi Xing (20141665)

“…The results of numerical simulations and sea trial experimental data indicate that the use of subarrays comprising 5 and 3 array elements, respectively, is sufficient to effectively estimate 12 source angles. …”

Spatial spectrum estimation for three algorithms. by Chuanxi Xing (20141665)

“…The results of numerical simulations and sea trial experimental data indicate that the use of subarrays comprising 5 and 3 array elements, respectively, is sufficient to effectively estimate 12 source angles. …”

Data_Sheet_1_Development of prognostic models for advanced multiple hepatocellular carcinoma based on Cox regression, deep learning and machine learning algorithms.CSV by Jie Shen (31533)

Data_Sheet_2_Development of prognostic models for advanced multiple hepatocellular carcinoma based on Cox regression, deep learning and machine learning algorithms.docx by Jie Shen (31533)

Face detection process based on AdaBoost algorithm. by Yingying Mei (13817440)

“…<p>Face detection process based on AdaBoost algorithm.</p>…”

Decision tree algorithms. by Mahbub E. Sobhani (22278967)

“…We have used decision tree (C4.5) as the base classifier of Random Forest and AdaBoost classifiers and naïve Bayes classifier as the base classifier of the Bagging model. …”

Holdout evaluation of performance on holdout test set between CatBoost and Logistic regression models. by Nowell M. Fine (13874645)

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Schematic diagram of the SARIMA algorithm flow. by Yongxin Dai (13796385)

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Noise reduction by the sliding average algorithm. by Yongxin Dai (13796385)

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5-fold cross-validation performance and statistical comparison between CatBoost and Logistic regression models. by Nowell M. Fine (13874645)

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Scatter diagram of different principal elements. by Jizhong Wang (7441697)

“…The experimental results show that the SSA-LightGBM model proposed in this paper has an average fault diagnosis accuracy of 93.6% after SSA algorithm optimization, which is 3.6% higher than before optimization. …”

Prediction of pharmaceuticals occurrence based on sales data and Machine learning algorithms. by Júlia Bijos (14489543)

“…</p><p dir="ltr"><b>Antibioticos/Carbamazepina</b>: contains the main codes of the prediction models to classify the occurrence concentrations of some antibiotics and Carbamazepine, by tree boosting algorithms.…”

The actual training effect of four algorithms on original photo data (All images are original images taken by the author). by Xiaojun Wang (50332)

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ROC curve stacking meta model gradient boosting. by Azhar Imran (17720751)

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