Forest types mapping is one of the most necessary elements in forest management and Silviculture treatments. Traditional methods such as field surveys are time-consuming and cost-intensive. Improving satellite data sources and classification methods offer new opportunities for obtaining more accurate forest biophysical maps. This research compares performance of three non-parametric and tree-ba...

In this study, a multiparametric magnetic resonance image (MRI) based technique of detecting prostate cancer is developed. A machine learning algorithm, based on random forest is used to classify the normal and cancer regions. Three features extracted from dynamic contrast enhanced MRI and two features extracted from diffusion tensor MRI is used to train the classifier. The classifier is traine...

Random forest is an ensemble classification algorithm. It performs well when most predictive variables are noisy and can be used when the number of variables is much larger than the number of observations. The use of bootstrap samples and restricted subsets of attributes makes it more powerful than simple ensembles of trees. The main advantage of a random forest classifier is its explanatory po...

We address the problem of estimating the pose of humans using RGB image input. More specifically, we are using a random forest classifier to classify pixels into joint-based body part categories, much similar to the famous Kinect pose estimator [11], [12]. However, we are using pure RGB input, i.e. no depth. Since the random forest requires a large number of training examples, we are using comp...

Ensemble learning techniques and in particular Random Forests have been one of the most successful machine learning approaches of the last decade. Despite their success, there exist barely suitable visualizations of Random Forests, which allow a fast and accurate understanding of how well they perform a certain task and what leads to this performance. This paper proposes an exemplar-driven visu...

Duplicate question pair detection plays a vital role in improving information retrieval systems and enhancing user experience. In this paper, we present comprehensive study on duplicate utilizing the Quora dataset. We employed machine learning techniques, specifically Random Forest XGBoost classifiers, to develop accurate models for identifying pairs. To improve performance of models, introduce...