A phishing attack is a sort of cyber assault in which the attacker sends fake communications to entice a human victim to provide personal information or credentials. Phishing website identification can assist visitors in avoiding becoming victims of these assaults. The phishing problem is increasing day by day, and there is no single solution that can properly mitigate all vulnerabilities, thus many techniques are used. In this paper, We have proposed an ensemble model that combines multiple base models with a voting technique based on the weights. Moreover, we applied feature selection methods and standardization on the dataset effectively and compared the result before and after applying any feature selection.

翻译：钓鱼攻击是一种网络攻击,攻击者在这种攻击中发送假通信,诱使受害人提供个人信息或证明。钓鱼网站识别可以帮助访问者避免成为这些攻击的受害者。钓鱼问题日复一日地增加,没有单一的解决办法能够适当减轻所有脆弱性,因此使用许多技术。在本文中,我们提出了一个组合模型,将多个基准模型与基于权重的投票技术结合起来。此外,我们有效地对数据集采用了选择方法和标准化,并在应用任何特征选择之前和之后对结果进行比较。