Random Forests (RF) is a successful classifier exhibiting performance comparable to Adaboost, but is more robust. The exploitation of two sources of randomness, random inputs (bagging) and random features, make RF accurate classifiers in several domains. We hypothesize that methods other than classification or regression trees could also benefit from injecting randomness. This paper generalizes...

As one of the world’s largest online retailers, Amazon.com has a sales volume of tens of billions dollars and as a result huge amounts of customer reviews accumulate. These reviews are great learning samples which could help promote commercial prediction and advertisement. Our project aims to build a multiclass classifier based on the customer reviews which are labeled by product categories in ...

This paper presents an approach to classify remote sensed data using a hybrid classifier. Random forest, Support Vector machines and boosting methods are used to build the said hybrid classifier. The central idea is to subdivide the input data set into smaller subsets and classify individual subsets. The individual subset classification is done using support vector machines classifier. Boosting...

--Nowadays, computer network systems plays gradually an important role in our society and economy. It became a targets of a wide array of malicious attacks that invariably turn into actual intrusions. This is the reason that computer security has become an essential concern for network administrators. In this paper, an exploration of anomaly detection method has been presented. The proposed sys...

Renal fibrosis is a common pathological pathway of progressive chronic kidney disease (CKD). However, kidney function parameters are suboptimal for detecting early fibrosis, and therefore, novel biomarkers are urgently needed. We designed a 2-stage study and constructed a targeted microarray to detect urinary mRNAs of CKD patients with renal biopsy and healthy participants. We analysed the micr...

This article presents a study on analyzing body movements by using a single accelerometer sensor. The investigated categories of body movements belong to the Laban Effort Framework: Strong-Light, Free-Bound and Sudden-Sustained. All body movements were represented by a set of activities used for data collection. The calculated accuracy of detecting the body movements was based on collecting dat...

Random forests (RF) is a popular general purpose classifier that has been shown to outperform many other classifiers on a variety of datasets. The widespread use of random forests can be attributed to several factors, some of which include its excellent empirical performance, scale and unit invariance, robustness to outliers, time and space complexity, and interpretability. While RF has many de...