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Bypass Apple Icloud Activation Lock On Iphone Ipads Ipod With SSH Trick(no Gsm) - Phones - Nairaland

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In iOS 7, Apple added a anti-theft feature called Activation Lock to the Find My iPhone service, which ties your iPhone, iPad or iPod touch with your Apple ID so that your lost or stolen iOS device, cannot be used or restored without the login credentials. The anti-lock feature has been quite effective, as law enforcement officials in the U.S. reported that the feature has helped in significantly reducing iPhone theft in major cities. We have come across several cases where users who have purchased used iPhones, and have been stuck with an usable iPhone because the previous owner has forgotten to turn off the Find my iPhone feature before shipping the device. well,if you are stucked in this icloud activation lock ,you can still remove it using this method but the gsm function will be disabled so only wifi and other features will work.this can be done within 10minute. you will need the following  (1) ssh jar  download ssh jar here. pls copy and paste the link in your browser an...
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PCA using R - KMO index and Bartlett's test

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Principal Component Analysis (PCA) is a dimension reduction technique. We obtain a set of factors which summarize, as well as possible, the information available in the data. The factors are linear combinations of the original variables. The approach can handle only quantitative variables. We have presented the PCA in previous tutorials. In this paper, we describe in details two indicators used for the checking of the interest of the implementation of the PCA on a dataset: the Bartlett's sphericity test and the KMO index. They are directly available in some commercial tools (e.g. SAS or SPSS). Here, we describe the formulas and we show how to program them under R. We compare the obtained results with those of SAS on a dataset. Keywords : principal component analysis, pca, spss, sas, proc factor, princomp, kmo index, msa, measure of sampling adequacy, bartlett's sphericity test, xlsx package, psych package, R software Components : VARHCA, PRINCIPAL COMPONENT ANALYSIS Tutorial : ...
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Cost-Sensitive Learning (slides)

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This course material presents approaches for the consideration of misclassification costs in supervised learning. The baseline method is the one for which we do not take into account the costs. Two issues are studied : the metric used for the evaluation of the classifier when a misclassification cost matrix is provided i.e. the expected cost of misclassification (ECM); some approaches which enable to guide the machine learning algorithm towards the minimization of the ECM. Keywords : cost matrix, misclassification, expected cost of misclassification, bagging, metacost, multicost Slides : Cost Sensitive Learning References : Tanagra Tutorial, " Cost-senstive learning - Comparison of tools ", March 2009. Tanagra Tutorial, " Cost-sensitive decision tree ", November 2008.
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