Machine Learning Methods of Effort Estimation and It’s Performance Evaluation Criteria

Effort estimation is important for the control, quality and success of any software development product. Most efficient categories of effort estimation is Expert judgment, Algorithmic estimation and Machine Learning. The aim of this paper is to present the comparative analysis between traditional techniques and Machine Learning (ML) techniques. Results show that ML methods give more accurate effort estimation as compared to the traditional methods of effort estimation. The comparisons of different Machine learning techniques are done in this paper to study that which ML method is more suitable in which situation. Keywords— Artificial intelligence (AI), Machine learning (ML), Genetic algorithm (GA), Case based reasoning (CBR), Artificial Neural Network (ANN)