Financial Transaction Anomaly Detection
Analyzing data from FI_Transactions.csv
SVM nu parameter (controls anomaly threshold)
↺
0.01
0.2
Number of KMeans clusters
↺
2
10
Detect Anomalies
Anomaly Distribution
SVM Anomaly Detection
KMeans Clustering
How to Use
Adjust the SVM nu parameter (controls anomaly detection sensitivity)
Choose the number of clusters for KMeans
Click 'Detect Anomalies' to analyze the data
Interpretation
The pie chart shows the proportion of normal vs anomalous transactions
The scatter plots visualize the clusters and anomalies
The AI insights provide expert analysis of detected anomalies
The table displays detailed information about detected anomalies