Predicting Stock Liquidity by Using Ensemble Data Mining Methods
نویسندگان
چکیده
منابع مشابه
Forecasting Stock Trend by Data Mining Algorithm
Stock trend forecasting is a one of the main factors in choosing the best investment, hence prediction and comparison of different firms’ stock trend is one method for improving investment process. Stockholders need information for forecasting firm’s stock trend in order to make decision about firms’ stock trading. In this study stock trend, forecasting performs by data mining algorithm. It sho...
متن کاملEnsemble Data Mining Methods
INTRODUCTION Ensemble Data Mining Methods, also known as Committee Methods or Model Combiners, are machine learning methods that leverage the power of multiple models to achieve better prediction accuracy than any of the individual models could on their own. The basic goal when designing an ensemble is the same as when establishing a committee of people: each member of the committee should be a...
متن کاملPredicting Type2 Diabetes Using Data Mining Algorithms
Background and purpose: Today, information systems and databases are widely used and in order to achieve higher accuracy and speed in making diagnosis, preventing the diseases, and choosing treatments they should be merged with traditional methods. This study aimed at presenting an accurate system for diagnosis of diabetes using data mining and a heuristic method combining neural network and pa...
متن کاملPredicting Student Performance by Using Data Mining Methods for Classification
Data mining methods are often implemented at advanced universities today for analyzing available data and extracting information and knowledge to support decision-making. This paper presents the initial results from a data mining research project implemented at a Bulgarian university, aimed at revealing the high potential of data mining applications for university management.
متن کاملGfKl Data Mining Competition 2005: Predicting Liquidity Crises of Companies
Data preprocessing and a careful selection of the training and classification method are key steps for building a predictive model with high performance. Here, we present the approach used for training and classification in our solutions submitted to the 2005 GfKl Data Mining Competition. The initial step of data preprocessing is described in the first part of this work. The task to be solved f...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Journal of the Korea Society of Computer and Information
سال: 2016
ISSN: 1598-849X
DOI: 10.9708/jksci.2016.21.6.009