Ciro Javier Diaz Penedo, Lucas Leonardo Silveira Costa
In this work we deal with the problem of grouping in headlines of the newspaper ABC (Australian Bro-adcasting Corporation) using unsupervised machine learning techniques. We present and discuss the results on the clusters found
Ciro Javier Diaz Penedo
In this work we address the problem of predicting the model of a camera based on the content of their photographs. We use two set of features, one set consist in properties extracted from a Discrete Wavelet Domain (DWD) obtained by applying a 4 level Fast Wavelet Decomposition of the images, and a second set are Local Binary Patterns (LBP) features from the after filter noise of images. The algorithms used for classification were Logistic regression, K-NN and Artificial Neural Networks
Ciro Javier Diaz Penedo, Lucas Leonardo Silveira Costa
We present a study of possible predictors based on four supervised machine learning models for the prediction of four mechanical properties of the main industrially used steels. The results were obtained from an experimental database available in the literature which were used as input to train and evaluate the models.