In this paper we describe our machine learning solution for the RecSys Challenge 2015. We have proposed a timeefficient two-stage cascaded classifier for the prediction of buy sessions and purchased items within such sessions. Based on the model, several interesting features found, and formation of our own test bed, we have achieved a reasonable score. Usage of Random Forests helps us to cope w...

In this paper, a new MAYO Index is presented for deeper analytics of the price and performance of IPL players in IPL season IX. The MAYO index is comprehensive in terms of including both price and performance in one index. This is in contrast to the popular indices like batting and bowling averages and MVPI that only measure performance. The index is created with the help of machine learning te...

In silico High Throughput Screening of large compound databases has become increasingly popular technology of finding valuable drug candidates, by applying a wide range of computational methods, such as machine learning [1]. In recent years, many comparative studies of different machine learning methods performance in ligandbased virtual screening have been reported [2,3]. In order to extend th...

One approach in classification tasks is to use machine learning techniques to derive classifiers using learning instances. The cooperation of several base classifiers as a decision committee has succeeded to reduce classification error. The main current decision committee learning approaches boosting and bagging use resampling with the training set and they can be used with different machine le...

Learning models of player behavior has been the focus of several studies. This work is motivated by better understanding of player behavior, a knowledge that can ultimately be employed to provide player-adapted or personalized content. In this paper, we propose the use of active learning for player experience modeling. We use a dataset from hundreds of players playing Infinite Mario Bros. as a ...

Predicting the outcome of a match has always been at the center of sports analytics. Indian Premier League (IPL), a professional Twenty20 (T20) cricket league in India, has established itself as one of the biggest tournaments in cricket history. In this paper, we propose a model to predict the winner at the end of each over in the second innings of an IPL cricket match. Our methodology not only...

This paper presents a supervised machine learning approach that aims at annotating those homograph word forms in WordNet that share some common meaning and can hence be thought of as belonging to a polysemous word. Using different graph-based measures, a set of features is selected, and a random forest model is trained and evaluated. The results are compared to other features used for polysemy ...

Abstract We consider predictions in longitudinal studies, and investigate the well known statistical mixed-effects model, piecewise linear model six different popular machine learning approaches: decision trees, bagging, random forest, boosting, support-vector neural network. In order to correlated data learning, effects is combined into traditional tree methods forest. Our focus performance of...

This article provides an overview of Supervised Machine Learning (SML) with a focus on applications to banking. The SML techniques covered include Bagging (Random Forest or RF), Boosting (Gradient GBM) and Neural Networks (NNs). We begin introduction ML tasks techniques. is followed by description of: i) tree-based ensemble algorithms including RF GBMs, ii) Feedforward NNs, iii) discussion hype...