1 to 10 of 46 Results
Jan 26, 2024 -
The Categorical Data Map - Replication Data
Comma Separated Values - 20.3 KB -
MD5: 869903971110c7c0c8db27d94199a943
A categorical dataset reconstructed from Yano et al. [KSDK11] describing property sales information from Singapor. It is manually reconstructed from the Parallel Sets visualization in Figure X of the publication by Yano et al. The reconstruction method is described in the Process... |
Sep 27, 2022 -
Replication Data for: "Slope-Dependent Rendering of Parallel Coordinates to Reduce Density Distortion and Ghost Clusters"
Tabular Data - 76.4 KB - 6 Variables, 850 Observations - UNF:6:dHHpAC3qiIpFizO+EWIYiA==
This file contains a synthetic dataset. It has five numeric dimensions. The data records of this dataset describe three classes also forming clusters in all dimensions. This dataset has 800 records. |
Sep 27, 2022 -
Replication Data for: "Slope-Dependent Rendering of Parallel Coordinates to Reduce Density Distortion and Ghost Clusters"
Tabular Data - 40.4 KB - 6 Variables, 450 Observations - UNF:6:9HyN/2jlcVdPuuq52hIwpQ==
This file contains a synthetic dataset. It has five numeric dimensions. The data records of this dataset describe three classes also forming clusters in all dimensions. This dataset has 400 records. |
Sep 27, 2022 -
Replication Data for: "Slope-Dependent Rendering of Parallel Coordinates to Reduce Density Distortion and Ghost Clusters"
Tabular Data - 22.5 KB - 6 Variables, 250 Observations - UNF:6:UEtK771CeC5HA0oYlouNfw==
This file contains a synthetic dataset. It has five numeric dimensions. The data records of this dataset describe three classes also forming clusters in all dimensions. This dataset has 200 records. |
Sep 27, 2022 -
Replication Data for: "Slope-Dependent Rendering of Parallel Coordinates to Reduce Density Distortion and Ghost Clusters"
Tabular Data - 13.5 KB - 6 Variables, 150 Observations - UNF:6:4FduUnJwRNYGTwDWaUbWVw==
This file contains a synthetic dataset. It has five numeric dimensions. The data records of this dataset describe three classes also forming clusters in all dimensions. This dataset has 100 records. |
Sep 27, 2022 -
Replication Data for: "Slope-Dependent Rendering of Parallel Coordinates to Reduce Density Distortion and Ghost Clusters"
Tabular Data - 114.0 KB - 9 Variables, 800 Observations - UNF:6:Xckxodnqrq7XKB7pkEERDQ==
This file contains a synthetic dataset. It has eight numeric dimensions. The data records of this dataset describe uniform noise. This dataset has 800 records. |
Sep 27, 2022 -
Replication Data for: "Slope-Dependent Rendering of Parallel Coordinates to Reduce Density Distortion and Ghost Clusters"
Tabular Data - 57.0 KB - 9 Variables, 400 Observations - UNF:6:YDkCJkbQEHrZ8rtkXyHDLQ==
This file contains a synthetic dataset. It has eight numeric dimensions. The data records of this dataset describe uniform noise. This dataset has 400 records. |
Sep 27, 2022 -
Replication Data for: "Slope-Dependent Rendering of Parallel Coordinates to Reduce Density Distortion and Ghost Clusters"
Tabular Data - 28.5 KB - 9 Variables, 200 Observations - UNF:6:NMP7PGDcDMEe7v0riGb5uQ==
This file contains a synthetic dataset. It has eight numeric dimensions. The data records of this dataset describe uniform noise. This dataset has 200 records. |
Sep 27, 2022 -
Replication Data for: "Slope-Dependent Rendering of Parallel Coordinates to Reduce Density Distortion and Ghost Clusters"
Tabular Data - 14.3 KB - 9 Variables, 100 Observations - UNF:6:UOGv/0HDWoM5g2/u8CzeSg==
This file contains a synthetic dataset. It has eight numeric dimensions. The data records of this dataset describe uniform noise. This dataset has 100 records. |
Sep 27, 2022 -
Replication Data for: "Slope-Dependent Rendering of Parallel Coordinates to Reduce Density Distortion and Ghost Clusters"
Tabular Data - 214.3 KB - 9 Variables, 1500 Observations - UNF:6:6RBJYOsc+MSxfcQI7nBFdw==
This file contains a synthetic dataset. It has eight numeric dimensions. The data records of this dataset describe four classes. The classes are not distinguishable in the three two dimensions. The remaining dimensions are the same as in synthetic-1-800.csv. This dataset has 800... |