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Machine Learning Techniques used for Prediction by IT Small and Medium-Sized Enterprises (SME) Structure Equation Modelling

Vidyadevi G. Biradar

Abstract


Approaches based on machine learning can be beneficial in a variety of contexts, including goal-oriented problems and narrowly focused problems requiring a lot of information. According to a general definition of "bundle space issues," a technique for learning that relies on the varying conditional conditions and changes of the specific issue being addressed by machine learning, a prophetic model is made by misuse machine learning approaches and grouped into imperfect, but non-blemished, modules. Engineers can use machine learning techniques to find knowledge that is useful when they are dealing with a wide variety of specialised challenges in a very specific sector. Their ability to break down material from completely unexpected angles grows as they build a foundation of productive ideas and different approaches to solving specific problems. For IT SME's, this study piece aims to provide light on the correlations between numerous variables. IBM SPSS is used for data analysis and interpretation in the study, which uses a well-structured questionnaire. We used the Structure Equation Modeling (SEM) technique to identify the most significant components.


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References


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