The Adept K-Nearest Neighbour Algorithm - An optimization to the Conventional K-Nearest Neighbour Algorithm
Journal Title: Transactions on Machine Learning and Artificial Intelligence - Year 2016, Vol 4, Issue 1
Abstract
This research aims to study the efficiency of a well-known classification algorithm, K-Nearest Neighbour, and suggest a new classification method, an optimised version than one of the existing classification method. The purpose of this research is to reduce the time taken by the existing K- Nearest Neighbour Classification method. The classification algorithm’s purpose is to identify the characteristics that indicate the class to which each document belongs. This pattern not only helps in understanding the existing data but also to predict how new instances will behave. Classification algorithms create classification models by examining already classified data (cases) and inductively finding a predictive pattern.
Authors and Affiliations
Anjali Jivani, Karishma Shah, Shireen Koul, Vidhi Naik
Keywords
Related Articles
- EP ID EP278362
- DOI 10.14738/tmlai.41.1876
- Views 55
- Downloads 0
Sentiment Analysis tool for Pharmaceutical Industry & Healthcare
Sentiment analysis (SA) is broadly used to analyze people’s opinions about a product or an event to identify breakpoints in public opinion. Particularly, pharmaceutical companies use SA to ensure they gain a competitive...
Bio-Inspired Temporal-Decoding Network Topologies for the Accurate Recognition of Spike Patterns
In this paper will be presented simple and effective temporal-decoding network topologies, based on a neuron model similar to the classic Leaky Integrate-and-Fire, but including the spike latency effect, a neuron propert...
Role of Management and Policy Issues in Computer Security: Rand Report R-609 within Organization
The need to provide strengthened Security for Information Systems within organization increases day after day seeing the large development of interconnection of the World Wide Web and the clear effect that results by the...
Handengineered Features vs Automated Features for Arabic Handwriting Recognition
This work aims to compare the learning features with Convolutional Neural Networks (CNNs) and the handcrafted features. In order to determine the relevant features among of those kinds. We consider our previous baseline...
Counterterrorism: Privately Clustering A Radical Social Network Data
The tradeoff between the needed or essential gathering and analysis of personal data and the privacy rights of individuals is now an important requirement under any counterterrorism program. The most famous and controver...