Machine learning-based classification techniques provide support for the decision making process in the field of healthcare, especially in disease diagnosis, prognosis and screening. Healthcare datasets are voluminous in nature and their high dimensionality problem comprises in terms of slower learning rate and higher computational cost. Feature selection is expected to deal with the high dimen...

The regularized random forest (RRF) was recently proposed for feature selection by building only one ensemble. In RRF the features are evaluated on a part of the training data at each tree node. We derive an upper bound for the number of distinct Gini information gain values in a node, and show that many features can share the same information gain at a node with a small number of instances and...

To distinguish the real pre-miRNAs from other hairpin sequences with similar stem-loops (pseudo pre-miRNAs), a hybrid feature which consists of local contiguous structure-sequence composition, minimum of free energy (MFE) of the secondary structure and P-value of randomization test is used. Besides, a novel machine-learning algorithm, random forest (RF), is introduced. The results suggest that ...

Meaningful relationships between forest structure attributes measured in representative field plots on the ground and remotely sensed data measured comprehensively across the same forested landscape facilitate the production of maps of forest attributes such as basal area (BA) and tree density (TD). Because imputation methods can efficiently predict multiple response variables simultaneously, t...

Objective The main purpose of this article is to choose the best predictive model for IVF/ICSI classification and to calculate the probability of IVF/ICSI success for each couple using Artificial intelligence. Also, we aimed to find the most effective factors for prediction of ART success in infertile couples. MaterialsAndMethods In this cross-sectional study, the data of 486 patients are colle...

Improvements in the acquisition of three-dimensional (3D) information from the Airborne Laser Scanner (ALS) increase its applications for studying Earth’s surface. The use of ALS data in natural resource inventories is still in an experimental stage in central Europe. Here, a survey was completed in Germany, where plot-level features from LANDSAT Thematic Mapper and ALS data were applied. An au...

Random forest (RF) is an ensemble classifier method, all decision trees participate in voting, some low-quality will reduce the accuracy of random forest. To improve forest, with larger degree diversity and higher classification are selected for voting. In this paper, RF based on Kappa measure improved binary artificial bee colony algorithm (IBABC) proposed. Firstly, used pre-pruning, from Then...

BACKGROUND With a large-scale electronic health record repository, it is feasible to build a customized patient outcome prediction model specifically for a given patient. This approach involves identifying past patients who are similar to the present patient and using their data to train a personalized predictive model. Our previous work investigated a cosine-similarity patient similarity metri...