A study reveals machine learning algorithms can predict compressive strength in concrete with waste glass powder, enhancing ...

Linear Regression Cost function in Machine Learning is "error" representation between actual value and model predictions. To minimize the error, we need to minimize the Linear Regression Cost ...

The Euclidean algorithm appears in Proposition 2 in Book 7 of Euclid’s The Elements. This article explores the relationship between some of the concepts and procedures that appear in this Proposition ...

such as machine learning algorithms, for more efficient parameter identification and system optimization. Overall, the resurgence of the old Babylonian algorithm in the modern context of non-linear ...

Here a machine learning algorithm will be trained to predict a liver disease in patients using a data-set collected from North East of Andhra Pradesh, India. Using machine learning models to predict ...

algorithm and the extreme learning machine (ELM), is proposed in this study, and the stresses of AZ80 magnesium alloy are predicted by the model through a 812-record dataset. The predicting results ...

Abstract: The k-vectors algorithm for learning regression functions proposed here is akin to the well-known k-means algorithm. Both algorithms partition the feature space, but unlike the k-means ...