SOTAVerified

General Classification

Algorithms trying to solve the general task of classification.

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 8451–8475 of 14581 papers

TitleStatusHype
UWB at SemEval-2018 Task 1: Emotion Intensity Detection in Tweets—0
Multi-Task Learning Framework for Mining Crowd Intelligence towards Clinical Treatment—0
PlusEmo2Vec at SemEval-2018 Task 1: Exploiting emotion knowledge from emoji and \#hashtags—0
T\"ubingen-Oslo at SemEval-2018 Task 2: SVMs perform better than RNNs in Emoji Prediction—0
Neural Network based Extreme Classification and Similarity Models for Product Matching—0
SemEval-2018 Task 3: Irony Detection in English Tweets—0
Learning Word Embeddings for Data Sparse and Sentiment Rich Data Sets—0
RNN for Affects at SemEval-2018 Task 1: Formulating Affect Identification as a Binary Classification Problem—0
Unrestricted Bridging Resolution—0
Persistence paths and signature features in topological data analysis—0
Adapted and Oversegmenting Graphs: Application to Geometric Deep Learning—0
Tandem Blocks in Deep Convolutional Neural Networks—0
Accurate and Efficient Similarity Search for Large Scale Face Recognition—0
A Classification approach towards Unsupervised Learning of Visual RepresentationsCode0
A Systematic Classification of Knowledge, Reasoning, and Context within the ARC Dataset—0
Domain Adaptation for MRI Organ Segmentation using Reverse Classification AccuracyCode0
Large-Margin Classification in Hyperbolic SpaceCode0
Imbalanced Ensemble Classifier for learning from imbalanced business school data set—0
A mixture model for aggregation of multiple pre-trained weak classifiers—0
HOPF: Higher Order Propagation Framework for Deep Collective ClassificationCode0
Greedy Attack and Gumbel Attack: Generating Adversarial Examples for Discrete Data—0
A Method Based on Convex Cone Model for Image-Set Classification with CNN Features—0
Efficient Traffic-Sign Recognition with Scale-aware CNN—0
Classification of volcanic ash particles using a convolutional neural network and probability—0
A Divide-and-Conquer Approach to Geometric Sampling for Active Learning—0
Show:102550
← PrevPage 339 of 584Next →
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