One of the well known and efficient techniques is decision trees, due to easy understanding structural output. But they may not always be easy to understand due to very big structural output. To overcome this short coming pruning can be used as a key procedure .It removes overusing noisy, ...
In this way, the generated decision tree is simplified. Through the above series of operations, we aim to establish a decision tree that fits well with the training set data and has a low complexity. As directly selecting the optimal decision tree from the possible decision trees is a NP-...
and can accept descriptive parameters of decision trees on different data mining set.Finally,it gets the ideal decision tree model.The results of experiments show that this algorithm balances the precision and complexity better,and meets the needs of medical diagnosis in different application context,...
ing the structure at the heart of a set of data. Ideally, such models can be used to predict properties of future data points and people can use them to analyze the domain from which the data originates. Decision trees and lists are potentially powerful predictors and embody an explic- ...
Classification is an important problem in data mining. Given a database of records, each with a class label, a classifier generates a concise and meaningful description for each class that can be used to classify subsequent records. A number of popular classifiers construct decision trees to gener...
Gama J (2004) Functional trees. Mach Learn 55(3):219–250 Article Google Scholar Kohavi R (1996) Scaling up the accuracy of naive-Bayes classifiers: A decision-tree hybrid. In: Proceedings of the second international conference on knowledge discovery and data mining (KDD-96). AAAI, Ca...
Then, the model is optimized, e.g., by converting floats to a fixed-point quantization, by pruning decision treesFootnote 4 etc. Third, the user chooses a backend that determines the target CPU’s properties, such as cache size, available memory, etc., as well as the desired ...
Decision tree classifier with integrated building 优质文献 相似文献 参考文献 引证文献PUBLIC: A Decision Tree Classifier that Integrates Building and Pruning Classification is an important problem in data mining. Given a database of records, each with a class label, a classifier generates a concise an...
Rule extraction from decision trees ensembles: new algorithms based on heuristic search and sparse group lasso methods 2017, International Journal of Information Technology and Decision Making CURE-SMOTE algorithm and hybrid algorithm for feature selection and parameter optimization based on random forests ...
Instead, we propose a novel classifier, namely, Cost-sensitive Boosting Pruning Trees (CBPT), which demonstrates a strong classification ability on two publicly accessible Twitter depression detection datasets. To comprehensively evaluate the classification capability of CBPT, we use additional three ...