Stencil printing is one of the key steps in reflow soldering technology, and by spread ultra-fine-pitch components, analysis this process essential. The stencil has been investigated a machine learning technique utilizing ensemble method boosted decision trees. phenomenon overfitting, which can alter prediction error trees also analyzed detail. training data set was acquired experimentally perf...

Convolutional Neural Networks are machine learning models that have proven abilities in many variants of tasks. This powerful model sometimes suffers from overfitting. paper proposes a method based on Reinforcement Learning for addressing this problem. In research, the parameters target layer Network take as state Agent section. Then gives some actions forming hyperbolic secant function. functi...

The analysis of high-dimensional survival data is challenging, primarily owing to the problem of overfitting, which occurs when spurious relationships are inferred from data that subsequently fail to exist in test data. Here, we propose a novel method of extracting a low-dimensional representation of covariates in survival data by combining the popular Gaussian process latent variable model wit...

The artificial neural network (ANN) has been applied to the various fields due its capability process complicated nonlinear functions involving a large amount of data. A pseudorandom binary sequence (PRBS) is commonly used train ANN since PRBS easily generated by using linear feedback shift register and correlation function which peaked at zero delay but almost other delays. However, when lengt...

Abstract Overfitting is a common and critical challenge for neural networks trained with limited dataset. The conventional solution software-based regularization algorithms such as Gaussian noise injection. Semiconductor noise, 1/ f in artificial neuron/synapse devices, which often regarded undesirable disturbance to the hardware (HNNs), could also play useful role suppressing overfitting, but ...

In most conditions, it is a problematic mission for machine-learning model with data record, which has various attributes, to be trained. There always proportional relationship between the increase of features and arrival overfitting susceptible model. That observation occurred since not all characteristics are important. For example, some could only cause noisier. Dimensionality reduction tech...