<span>In the production, efficient employment of machines is realized as a source industry competition and strategic planning. In manufacturing industries, data silos are harvested, which needful to be monitored deployed an operational tool, will associate with right decision-making for minimizing maintenance cost. However, it complex prioritize decide between several results. This articl...

Classification is one of the most important task in application areas of artificial neural networks (ANN).Training neural networks is a complex task in the supervised learning field of research. The main difficulty in adopting ANN is to find the most appropriate combination of learning, transfer and training function for the classification task. We compared the performances of three types of tr...

This paper presents two instance-level transfer learning based algorithms for cross lingual opinion analysis by transferring useful translated opinion examples from other languages as the supplementary training data for improving the opinion classifier in target language. Starting from the union of small training data in target language and large translated examples in other languages, the Tran...

Constructive learning algorithms o er an approach to incremental construction of near-minimal arti cial neural networks for pattern classi cation. Examples of such algorithms include Tower, Pyramid, Upstart, and Tiling algorithms which construct multilayer networks of threshold logic units (or, multilayer perceptrons). These algorithms di er in terms of the topology of the networks that they co...

This paper compares the performance of large scale Support Vector Machine training algorithms tested on a language recognition task. We analyze the behavior of five SVM approaches for training phonetic and acoustic models, and we compare their performance in terms of number of iterations to reach convergence, training time and scalability towards large databases. Our results show that the accur...

This paper presents work which extends previous corpus-based work on training Machine Learning Algorithms to perform Prepositional Phrase attachment. Besides recreating others’ experiments to see how algorithms’ performance changes with the number of training examples and using n-fold cross-validation to produce more accurate error rates, we implemented our own vanilla Machine Learning Algorith...

Remote sensing image analysis can be carried out at the per-pixel (hard) and sub-pixel (soft) scales. The former refers to the purity of image pixels, while the latter refers to the mixed spectra resulting from all objects composing of the image pixels. The spectral unmixing methods have been developed to decompose mixed spectra. Data-driven unmixing algorithms utilize the reference data called...