Abstract Tensor network quantum machine learning (QML) models are promising applications on near-term hardware. While decoherence of qubits is expected to decrease the performance QML models, it unclear what extent diminished can be compensated for by adding ancillas and accordingly increasing virtual bond dimension models. We investigate here competition between classification two with an anal...

The paper focuses on predicting the Nifty 50 Index by using 8 Supervised Machine Learning Models. techniques used for empirical study are Adaptive Boost (AdaBoost), k-Nearest Neighbors (kNN), Linear Regression (LR), Artificial Neural Network (ANN), Random Forest (RF), Stochastic Gradient Descent (SGD), Support Vector (SVM) and Decision Trees (DT). Experiments based historical data of Indian Sto...

machine-part family formation is one of major applications of group technology (gt). the machine cell formation problem in cellular manufacturing system (cms) involves the decomposition of the manufacturing system into machine cells. part families are identified such that they are fully processed within a machine cell. the problem of cell design is a very complex task with wide ranging implicat...

A method for counterfactual explanation of machine learning survival models is proposed. One the difficulties solving problem that classes examples are implicitly defined through outcomes a model in form functions. condition establishes difference between functions original example and introduced. This based on using distance mean times to event. It shown can be reduced standard convex optimiza...