Comparative study of Glass Type Classification using Machine Learning

Abstract

The glass sector is regarded as one of the world's most important. Glass is used in a multitude of scenarios, ranging from water bottles to X-Ray and Gamma Ray shielding. This is a transparent, non-crystalline, amorphous solid. Glass is used in a variety of ways, and investigators should be able to identify which type of glass is present during a crime scene assessment. We'll utilize the internet dataset and machine learning to resolve the greater than disadvantage in order to find out what type of glass it is. Machine learning algorithms such as with the Support Vector Machine (SVM) algorithm, the Random Forest methodology, the logistical Regression algorithm, and the AdaBoost classifier, as well as the Gradient Boosting classifier, will be exploited. Random Forest performed the best in glass classification out of all the computational rules. Flat glass is now available in a variety of specialized shapes for usage in various applications and products. The process of flotation is used to make flat glass. There are, however, many specific procedures that may be used to give it a range of special forms. The trade is able to meet the needs and desires of the automobile, construction, and solar power industries by using this strategy. However every product and application needs a unique glass, for that reason within the industrial world there square measure differing kinds of glass that may create your domestic and industrial life easier.