<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 ktvwwo"><div style="min-height: 80px;"><div class="sc-etVRix jqYJaa sc-bMmLMY ZURWJ"><h1>Introduction</h1>

<p>This includes the processed NumPy arrays of training and testing datasets which intends to classify the skin cancer images into benign and malignant.</p>

<h1>Content</h1>

<h3>train_dataset</h3>

<p>x_train.npy: A NumPy array created with skin cancer images by setting dimensions (2000, 128, 128, 1) including benign and malignant images for training purposes.</p>

<p>y_train.npy: Includes the corresponding category (benign - 0, malignant - 1) of x_train.npy with dimensions (2000, 2).</p>

<h3>test_dataset:</h3>

<p>x_test.npy: A NumPy array created with skin cancer images by setting dimensions (120, 128, 128, 1) including benign and malignant images for testing purposes.</p>

<p>y_test.npy: Includes the corresponding category (benign - 0, malignant - 1) of x_test.npy with dimensions (120, 2).</p>

<h1>Acknowledgments</h1>

<p>Created the dataset involving ISIC-Archive (<a rel="noreferrer nofollow" aria-label="https://www.isic-archive.com/#!/topWithHeader/onlyHeaderTop/gallery) (opens in a new tab)" target="_blank" href="https://www.isic-archive.com/#!/topWithHeader/onlyHeaderTop/gallery)">https://www.isic-archive.com/#!/topWithHeader/onlyHeaderTop/gallery)</a>.</p></div></div></div>