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Semi-supervised Embedding in Attributed Networks with Outliers
SEANO is a semi-supervised embedding framework for attributed networks with outliers. -
Heart Disease
The dataset used in the paper is a real-world dataset for outlier explanation. The dataset is used to evaluate the performance of the proposed methods. -
Readmission
The dataset used in the paper is a real-world dataset for outlier explanation. The dataset is used to evaluate the performance of the proposed methods. -
Food industry dataset
The dataset used in the paper is a bivariate dataset with two color signals measured on organic sultana raisin samples. -
Non-elliptical dataset
The dataset used in the paper is a non-elliptical dataset with 1000 bivariate observations, generated from a t copula with Pearson correlation 0.1 and ν = 1 degrees of freedom,... -
Detecting outliers with Poisson image interpolation
The PII dataset is a benchmark for outlier detection in medical images -
Synthetic datasets
The authors used synthetic datasets with temporal dependencies and actions. The datasets have 1 million examples, with dimensionality of X t = 20 and ground-truth f is a random... -
Outlier Detection on Sensor Data
The dataset used for outlier detection on sensor data from temperature and humidity sensors deployed in sensorized farms and manufacturing units on Purdue University's campus.
