SOTAVerified

General Classification

Algorithms trying to solve the general task of classification.

Papers

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Showing 8126–8150 of 14581 papers

TitleStatusHype
Positive Semidefinite Metric Learning with Boosting—0
Positive semidefinite support vector regression metric learning—0
Positive-Unlabeled Classification under Class Prior Shift and Asymmetric Error—0
POS Tagging and its Applications for Mathematics—0
Post Selection Inference with Kernels—0
Potential and Limitations of Cross-Domain Sentiment Classification—0
Power Data Classification: A Hybrid of a Novel Local Time Warping and LSTM—0
Power efficient Spiking Neural Network Classifier based on memristive crossbar network for spike sorting application—0
Power Normalizations in Fine-grained Image, Few-shot Image and Graph Classification—0
Power Optimizations in MTJ-based Neural Networks through Stochastic Computing—0
Power System Disturbance Classification with Online Event-Driven Neuromorphic Computing—0
Power System Event Identification based on Deep Neural Network with Information Loading—0
PPDB 2.0: Better paraphrase ranking, fine-grained entailment relations, word embeddings, and style classification—0
PPP: Joint Pointwise and Pairwise Image Label Prediction—0
PR2: A Language Independent Unsupervised Tool for Personality Recognition from Text—0
Practical Contextual Bandits with Regression Oracles—0
Practical Evaluation of Out-of-Distribution Detection Methods for Image Classification—0
Practical Introduction to Clustering Data—0
Practical method to reclassify Web of Science articles into unique subject categories and broad disciplines—0
Practical Perspectives on Quality Estimation for Machine Translation—0
Practical Processing of Mobile Sensor Data for Continual Deep Learning Predictions—0
Practical Selection of SVM Supervised Parameters with Different Feature Representations for Vowel Recognition—0
PRADO: Projection Attention Networks for Document Classification On-Device—0
Pragmatic classification of movement primitives for stroke rehabilitation—0
Precise Statistical Analysis of Classification Accuracies for Adversarial Training—0
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All datasetsXORirisActivityFashion-MNISTISOLETMice ProteinMNISTWine

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1KNNAccuracy93.1—Unverified
2RFAccuracy92.96—Unverified
3CARTAccuracy92.82—Unverified
4LDAAccuracy77.22—Unverified
#ModelMetricClaimedVerifiedStatus
1MONT3Accuracy100—Unverified
2XBNETAccuracy100—Unverified
#ModelMetricClaimedVerifiedStatus
1CAEAccuracy42—Unverified
#ModelMetricClaimedVerifiedStatus
1CAEAccuracy67.7—Unverified
#ModelMetricClaimedVerifiedStatus
1CAEAccuracy68.5—Unverified
#ModelMetricClaimedVerifiedStatus
1CAEAccuracy13.4—Unverified
#ModelMetricClaimedVerifiedStatus
1CAEAccuracy90.6—Unverified
#ModelMetricClaimedVerifiedStatus
1MONT3Accuracy100—Unverified