{
  "annotation_id": "2a8472da-5434-4b0b-a16c-290da6c22be4",
  "date_created": "2026-03-02T18:01:35.851000Z",
  "date_modified": "2026-03-02T18:01:35.851000Z",
  "file_hash": "f6be228d6a85c631512cc1c1e1e355e2c55ef6dac0de1066d26fd5c226f56d0f",
  "private": false,
  "record": {
    "abstract": "We present a novel method for finding low dimensional views of high\ndimensional data: Targeted Projection Pursuit. The method proceeds by finding\nprojections of the data that best approximate a target view. Two versions of\nthe method are introduced; one version based on Procrustes analysis and one\nbased on a single layer perceptron. These versions are capable of finding\northogonal or non-orthogonal projections respectively. The method is\nquantitatively and qualitatively compared with other dimension reduction\ntechniques. It is shown to find two-dimensional views that display the\nclassification of cancers from gene expression data with a visual separation\nequal to, or better than, existing dimension reduction techniques.",
    "arxiv_id": "q-bio/0605028",
    "authors": [
      "J. Faith",
      "R. Mintram",
      "M. Angelova"
    ],
    "categories": [
      "q-bio.QM"
    ],
    "title": "Targeted Projection Pursuit for Gene Expression Data Classification and   Visualisation",
    "url": "https://arxiv.org/abs/q-bio/0605028"
  },
  "schema_id": "dorsal/arxiv",
  "source": {
    "execution_id": "2e2369bf-4556-4e75-9fb6-e3148d196bc0",
    "id": "arXiv Dataset IDs",
    "type": "Model",
    "variant": "snapshot-2026-03-01",
    "version": "0.1.0"
  },
  "user_id": 1000002
}