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<div class="sc-jegwdG lhLRCf"><div class="sc-UEtKG dGqiYy sc-flttKd cguEtd"><div class="sc-fqwslf gsqkEc"><div class="sc-cBQMlg kAHhUk"><h2 class="sc-dcKlJK sc-cVttbi gqEuPW ksnHgj">About Dataset</h2></div></div></div><div class="sc-davvxH eCVTlP"><div class="sc-jCNfQM dTyvWO"><div style="min-height: 80px;"><div class="sc-etVRix jqYJaa sc-gVIFzB gQKGyV"><p>Breast Cancer Dataset Data Card</p>





  
  

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<p>Description:<br>





  
  

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The Breast Cancer dataset consists of features computed from a digitized image of a fine needle aspirate (FNA) of a breast mass. These features describe characteristics of cell nuclei present in the image.</p>





  
  

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<p>Attributes:</p>





  
  

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<p>ID: Unique identifier for each sample.<br>





  
  

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Diagnosis: The diagnosis of the breast mass (Malignant - M, Benign - B).<br>





  
  

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Radius Mean: Mean of distances from the center to points on the perimeter.<br>





  
  

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Texture Mean: Standard deviation of gray-scale values.<br>





  
  

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Perimeter Mean: Mean size of the core tumor.<br>





  
  

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Area Mean: Mean area of the core tumor.<br>





  
  

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Smoothness Mean: Mean smoothness of the cell nuclei.<br>





  
  

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Compactness Mean: Mean compactness of the cell nuclei.<br>





  
  

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Concavity Mean: Mean concavity of the cell nuclei.<br>





  
  

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Concave Points Mean: Mean number of concave portions of the contour.<br>





  
  

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Symmetry Mean: Mean symmetry of the cell nuclei.<br>





  
  

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Fractal Dimension Mean: Mean "coastline approximation" - 1.<br>





  
  

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Target Variable:</p>





  
  

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<p>Diagnosis: Malignant (M) or Benign (B).<br>





  
  

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Usage:<br>





  
  

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This dataset can be used to develop predictive models to classify breast masses as either malignant or benign based on the provided features.</p></div></div></div>