Classification is used in many fields today, and for most of them machine learning algorithms can be used to make a decision. This article investigates the effects of different sizes of training and test datasets on the accuracy of classification using both classical k-nearest neighbors (kNN) ...
KNN classifier for human emotion from EEG eegemotion-recognitionknn-classificationdeap-dataset UpdatedNov 19, 2020 Python IoBT-VISTEC/Deep-Learning-for-EEG-Based-Biometrics Star16 Affective EEG-Based Person Identification Using the Deep Learning Approach (IEEE Transactions on Cognitive and Developmental Sy...
Large video dataset for action classification. Actions classified and labeled. 45M frames of video Video, images, text Classification, action detection 2013 [50][51] Y. Jiang et al. Activitynet Large video dataset for activity recognition and detection. Actions classified and labeled. 10,024 Video...
The CFS over other methods leads to a good overall performance in most cases, especially when the KNN classifier is used for P300 component classification, illustrating that the ERP component may be applied as a tool for auxiliary diagnosis of depression10. Hu et al. suggested that a negatively...
# First we construct our Classification Model knn = neighbors.KNeighborsClassifier(n_neighbors=nbrs) # Next we train our model knn.fit(Xtrain, Ytrain.values.ravel()) # Finally, we test our model result = knn.predict(Xtest) y_true=list(result) ...
[20], and Gray Level Co-occurrence Matrix (GLCM) [29] as features extraction and K Nearest Neighbor (KNN), Support Vector Machine (SVM), and Decision Tree (DT) as classifiers. In addition, the feature extraction time was calculated for a single image in seconds under the three feature ...
其中 kNN(xi) 表示数据集 D 中实例 xi 的k 个最近邻居的集合。kDN(xi) 的值越高,该样本就被来自不同类的更多实例包围,它的分类就越困难。对于具有 nD 个实例和 mD 个输入特征的数据集 D,该度量的开销为 O(nD⋅mD)。Disjunct Class Percentage(分离类百分比,DCP):使用 D 构建决策树,计算在 Disjunct ...
This repository is for the work I did in machine learning using Python. svmlinear-regressionmachine-learning-algorithmskmeans-clusteringbreast-cancer-wisconsinknn-classificationmean-shifttitanic-dataset UpdatedApr 8, 2018 Python Udacity Data Analyst Nanodegree Project : Create a Tableau Story - Titanic Da...
CAST-B/16 General Action Video Anomaly Detection Something-Something V2 Pooled Image Level kNN Action Classification Something-Something V2 CAST-B/16 Video Classification Something-Something V2 MSNet-R50En Show all 8 benchmarks Papers Dataset Loaders ...
kNN Classification - 89.98% Accuracy Random Forest Classification - 90.39% Accuracy Decision Tree Classification - 86.66% Accuracy Gradient Boosting Classification - 71.46% Accuracy Hyperparameter tuned the RandomForestClassification - 95.77% and GradientBoostingClassification - 95.21%. ...