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Showing posts from June, 2015

iCloud Bypass Tutorial With a Free Tool

Have you searched for how to bypass iCloud lock ? There are dozens of different sites saying that they can unlock iCloud activation lock , but we’ll explain what these sites do when they claim you can use an iCloud bypass tool to unlock iCloud lock for your iPhone 6, iPhone 6 Plus, iPhone 5s, iPhone 5 and other iPhone models. The solution on how to Bypass iCloud Activation Lock iOS 8 and iOS 7 is not as simple as these site explain and you can’t always iCloud unlock iPhone or iCloud unlock iPad. Y ou can also watch the video on How to Unlock Activation Lock with no password. Some of these sites claim they can “Remove Completely Apple iCloud Lock to bypass icloud lock and get new Apple ID and password.” But this is not true, to remove or bypass iCloud activation lock, you need the account information of the previous user. You can read more about how to remove Find My iPhone, read iCloud: Remove Find My iPhone . The iOS iCloud bypas s for the iPhone and iPad is something Apple owne

Cross-validation, leave-one-out, bootstrap (slides)

In supervised learning, it is commonly accepted that one should not use the same sample to build a predictive model and estimate its error rate. The error obtained under these conditions - called resubstitution error rate - is (very often) too optimistic, leaving to believe that the model will present an excellent performance in prediction. A typical approach is to divide the data into 2 parts (holdout approach): a first sample, said train sample is used to construct the model; a second sample, said test sample, is used to measure its performance. The measured error rate reflects honestly the model behavior in generalization. Unfortunately, on small dataset, this approach is problematic. By reducing the amount of data presented to the learning algorithm, we cannot learn correctly the underlying relation between the descriptors and the class attribute. At the same time, the part devoted to testing remains limited, the measured error has high variance. In this document, I present resampl