classification accuracies
Snoring sounds’ statistical characteristics depend on anthropometric parameters
... for classification of people into two groups of OSA and simple ...on classification accuracies of meth- ods using SS features for screening OSA from simple snorers when anthropometric parameters are ...
10
PLANT GROWTH MODELING OF ZINNIA ELEGANS JACQ USING FUZZY MAMDANI AND L SYSTEM APPROACH WITH MATHEMATICA
... multivariate classification models based on spectroscopic ...sPLS-DA classification accuracies were used for evaluating and comparing the spectral preprocessing ...
10
“ANFIS BASED MODEL IN DECISION MAKING TO OPTIMIZE THE PROFIT IN FARM CULTIVATION”
... This paper contributes to compare the results of decision making of maximizing profit in farm cultivation namely rice using ANFIS model and Multi Objective Linear Programming Problem by optimization method. Data is ...
7
Assessment of L-Band SAR Data at Different Polarization Combinations for Crop and Other Landuse Classification
... good classification accuracies as produced by full- polarimetric data, hybrid polarimetric data with circular polarization transmit and linear polarization receive mode has great potential for polarimetric ...
19
Sleep Apnea Detection Using Adaptive Neuro Fuzzy Inference System
... The classification accuracies due to the obtained 1-minute and 3-minute based classification results for chest, nasal and abdominal respiratory signals are given in Tables 1 and 2, ...
5
ReAl-LiFE: Accelerating the Discovery of Individualized Brain Connectomes on GPUs
... the classification analysis. (Bottom) Classification accuracies based on number of fibers for the un- pruned connectome (Pre-LiFE; magenta bar), connection weights with LiFE pruning (brown bar), with ...
9
Development of Interest in Science and Interest in Teaching Elementary Science: Influence of Informal, School, and Inquiry Methods Course Experiences
... of classification accuracies and classification results from individual ...fuzzy classification fusion model (GFFSVM) in which the real-coded GAs are applied to tune the input membership ...
127
Automatic Monitoring of Activities of Daily Living based on Real life Acoustic Sensor Data: a preliminary study
... This work presents a distributed acoustic sensor network for the observation of activities of daily living from elderly on the basis of the corresponding audio and ultrasound data. The baseline system that is proposed ...
6
BFSSGA: Enhancing the Performance of Genetic Algorithm using Boosted Filtering Approach
... average classification accuracy values, standard deviation from average values and the highest classification accuracy ...highest classification accuracies and better average ...
6
Linguistic Structured Sparsity in Text Categorization
... prove classification accuracies compared to standard regularizers that penalize fea- tures in isolation (such as lasso, ridge, and elastic net regularizers) on a range of datasets for various text ...
11
Idendifying Eye Movements using Neural Networks for Human Computer Interaction
... Classification accuracies varied from 90.99% and 90.10% for convolution features and 90.88% and 89.92% for SVD features using time delay neural network and feed forward neural network re[r] ...
9
A Hybrid Classification Model For Diabetes Dataset Using Decision Tree
... best classification accuracies are obtained are different for various parameter in the dataset, the commonly accepted one is FB tree because the corresponding classification accuracies are ...
7
New Textural Extraction Method Using Rolling Ball and Riping Membrane Transforms
... image classification for land use classes were ...two classification sets were ...the classification accuracies of the land use ...spectral/spatial classification data indicated that ...
9
Inter-platform concordance of gene expression data for the prediction of chemical mode of action
... of classification assessing the predictability of classes defined by the chemical mode of action (MOA), using a set of classifiers trained in two genomic plat- ...weak classification accu- racies for a set ...
14
Studying SVM Method's Scalability Using Text Documents
... A major issue that occurs in all classification and clustering algorithms is that they are reluctant to fit in the real spaces. For instance they have a problem dealing with new documents for which none of the ...
10
Adapting myoelectric control in real-time using a virtual environment
... [29]. Classification and propor- tional control speed were processed on the embedded system and transmitted over Wi-Fi to a desktop com- puter (Alienware Aurora R5, Intel i7–6700, 16 GB RAM, NVIDIA GTX ...
12
Complementarity Between Sentinel-1 and Landsat 8 Imagery for Built-Up Mapping in Sub-Saharan Africa
... landscapes such as in Gao or Katsina. This complementarity was correctly modeled by the RF classifier and, as a result, the fusion schemes presented high accuracies in both bare lands and vegetated areas. ...
13
EEG signal classification: an application to the emotion-related brain anticipatory activity.
... several classification problems of neurophysiological ...activity. Classification performance of three different classifiers (LDA, SVM and kNN) was compared using both spectral and temporal ...in ...
26
Features Extraction and Depression Level Prediction by using EEG Signals
... By using filters in MATLAB low pass filter, high pass filter and notch filter particular band of frequency can be selected. Identifying the EEG data feature in order to achieve better results for classifying EEG data ...
9
DNA Sequence Classification: It’s Easier Than You Think: An open-source k-mer based machine learning tool for fast and accurate classification of a variety of genomic datasets
... We consider the set of whole human mitochondrial genomes, partitioned by haplogroup from the MitoMap project [107]. Since this dataset has just under 28,000 sequences, and in order to avoid issues with class size ...
107