Machine Learning (predictive analytics) fully solved 2024

Machine Learning Machine learning is defined as an automated process that extracts patterns from data. Supervised Machine Learning To build the models used in predictive data analytics applications, we used supervised machine learning. Supervised machine learning techniques automatically learn a model of the relationship between a set of descriptive features and a target feature based on a set of historical examples, or instances. We can use this model to make predictions for new instances. Machine learning algorithms Machine learning algorithms automate the process of learning a model that captures the relationship between the descriptive features and the target feature in a dataset. Consistent model A model is consistent with the dataset if there are no instances in the dataset for which the model does not make a correct prediction. Ill-posed problem An ill-posed problem is a problem for which a unique solution cannot be determined using only the information that is available. 2 problems why just searching for models that are consistent with the data 1. With large datasets, it is likely that there will be noise in the data, and prediction models that are consistent with noisy data will make incorrect predictions. 2. In he vast majority of machine learning projects, the training set represents only a small sample of the possible set of instances in the domain.