In this paper, authors have proposed an interpretable feature recommendation method for solving sensor signal analytics problem machine maintenance domain. The basic Wide learning based architecture for feature recommendation is out of the scope of discussion in this paper and authors have emphasized on the interpretation of the recommended features and how this human in loop interpretation sys...

the main purpose of this study was to investigate experts’ perceptions of barriers to organic farming in ministry of agriculture. the population of this survey consisted of the experts in department of horticultural products, ministry of agriculture in 2008-2009 (n= 160). using of kerejcie and morgan table, 113 experts were selected through stratified random sampling method. validity of the ins...

Neural networks are powerful tools for classification and regression in static environments. This paper describes a technique for creating an ensemble of neural networks that adapts dynamically to changing conditions. The model separates the input space into four regions and each network is given a weight in each region based on its performance on samples from that region. The ensemble adapts d...

The introduction of recommender systems to existing online services is now practically inevitable, with the increasing number of items and users on online services. Popular recommender systems have successfully implemented satisfactory systems, which are usually based on collaborative filtering. However, collaborative filtering-based recommenders suffer from well-known problems, such as popular...

Mixture of Experts (MoE) is a popular framework in the fields of statistics and machine learning for modeling heterogeneity in data for regression, classification and clustering. MoE for continuous data are usually based on the normal distribution. However, it is known that for data with asymmetric behavior, heavy tails and atypical observations, the use of the normal distribution is unsuitable...

ÐThis article introduces a new tool for exploratory data analysis and data mining called Scale-Sensitive Gated Experts (SSGE) which can partition a complex nonlinear regression surface into a set of simpler surfaces (which we call features). The set of simpler surfaces has the property that each element of the set can be efficiently modeled by a single feedforward neural network. The degree to ...

We describe a neural network architecture designed to learn the musical structure of jazz melodies over chord progressions, then to create new melodies over arbitrary chord progressions from the resulting connectome (representation of neural network structure). Our architecture consists of two sub-networks, the interval expert and the chord expert, each being LSTM (long short-term memory) recur...

The ‘theorise-inquire’ technique is described, which supports the testing of both experts’ hunches and the quality of data sources. This technique is useful for the identification of data sources and data gaps by domain experts. We describe and illustrate the use of group contrasts, an analysis technique that allows an expert to explore and interpret repertory grids interactively to find signif...