Most of the real world problems are concerned with assignment of multiple target labels to the instances. The proposed model aims to increase the accuracy by incorporating supervised and semi supervised learning. K Means clustering is employed which creates K clusters based on the initialization of cluster centroids. Datasets are clustered based on its distribution in the Euclidean space. Clust...

We live in a digitized era where our daily life depends on using online resources. Businesses consider the opinions of their customers, while people rely reviews/comments other users before buying specific products or services. These are usually provided non-normative natural language within different contexts and domains (in social media, forums, news, blogs, etc.). Sentiment classification pl...

Species distribution models are scarcely applicable to invasive species because of their breaking of the models' assumptions. So far, few mechanistic, semi-mechanistic or statistical solutions like dispersal constraints or propagule limitation have been applied. We evaluated a novel quasi-semi-mechanistic approach for regional scale models, using historical proximity variables (HPV) representin...

Nowadays, most people obtain information from social media networks, where news accompanied by photos and videos attracts readers more than traditional ones. However, these advantages are often misused some publishers to disseminate fake rapidly, thereby adversely affecting individuals societies. Thus, the early detection of posts is crucial. Developing an automatic content-based detector ideal...

This work reports the results of four ensemble approaches with the M5 model tree as the base regression model to anticipate Sodium Adsorption Ratio (SAR). Ensemble methods that combine the output of multiple regression models have been found to be more accurate than any of the individual models making up the ensemble. In this study additive boosting, bagging, rotation forest and random subspace...