<div class="sc-cmRAlD dkqmWS"><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-jgvlka jFuPjz"><div class="sc-gzqKSP tNtjD"><div style="min-height: 80px;"><div class="sc-etVRix jqYJaa sc-bMmLMY ZURWJ"><p>This dataset contains 600 entries with 9 attributes related to prostate cancer diagnosis. The dataset includes measurements of tumor characteristics such as radius, texture, perimeter, area, smoothness, compactness, symmetry, and fractal dimension. These numerical features help in identifying the nature of the tumor.<br>

The target variable, "diagnosis_result", is categorical and has two classes:</p>

<ul>

<li>M (Malignant) – Cancerous tumor</li>

<li>B (Benign) – Non-cancerous tumor<br>

This dataset can be used for predictive modeling to classify prostate cancer tumors using machine learning algorithms.</li>

</ul>

<ol>

<li>radius – The average distance from the center to the tumor boundary. A larger radius may indicate a larger tumor size – float data type</li>

<li>texture – Variation in intensity levels within the tumor image. It helps in identifying structural differences in the tissue – float data type</li>

<li>perimeter – The length of the tumor boundary. A higher value can be associated with an irregular or larger tumor shape – float data type</li>

<li>area– The total size of the tumor. A larger area may indicate a more advanced stage of cancer – float data type</li>

<li>smoothness– Measures how smooth or irregular the tumor surface is. Lower values suggest a smoother boundary, while higher values indicate irregular growth – float data type</li>

<li>compactness – A ratio that compares the perimeter and area of the tumor. Higher compactness may indicate a denser, more aggressive tumor – float data type</li>

<li>symmetry– Evaluates how symmetrical the tumor shape is. Asymmetry can be a sign of malignancy – float data type</li>

<li>fractal_dimension – A mathematical measure of tumor complexity. Higher values indicate a more complex tumor structure – float data type</li>

<li>diagnosis_result– The classification label indicating whether the tumor is Malignant (M) (cancerous) or Benign (B) (non-cancerous) – object (categorical: 'M' or 'B') data type</li>

</ol></div></div></div>