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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>
+<p>Description:<br>
+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>
+<p>Attributes:</p>
+<p>ID: Unique identifier for each sample.<br>
+Diagnosis: The diagnosis of the breast mass (Malignant - M, Benign - B).<br>
+Radius Mean: Mean of distances from the center to points on the perimeter.<br>
+Texture Mean: Standard deviation of gray-scale values.<br>
+Perimeter Mean: Mean size of the core tumor.<br>
+Area Mean: Mean area of the core tumor.<br>
+Smoothness Mean: Mean smoothness of the cell nuclei.<br>
+Compactness Mean: Mean compactness of the cell nuclei.<br>
+Concavity Mean: Mean concavity of the cell nuclei.<br>
+Concave Points Mean: Mean number of concave portions of the contour.<br>
+Symmetry Mean: Mean symmetry of the cell nuclei.<br>
+Fractal Dimension Mean: Mean "coastline approximation" - 1.<br>
+Target Variable:</p>
+<p>Diagnosis: Malignant (M) or Benign (B).<br>
+Usage:<br>
+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>
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