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I am trying to find the correlation of all the columns in this dataset excluding qualityand then plot the frequency distribution of wine quality.

I am doing it the following way, but how do I remove quality?

I am trying to implement NLPCA (Nonlinear PCA) on a data set using the homals package in R but I keep on getting the following error message:

Error in dimnames(x) <- dn : length of 'dimnames' [1] not equal to array extent

The data set I use can be found in the UCI ML Repository and it's called dat when imported in R: https://archive.ics.uci.edu/ml/datasets/South+German+Credit+%28UPDATE%29

Here is my code (some code is provided once the data set is downloaded):

I expect identical results calculating a CI for a proportion using qbinom and binom.test, but they are actually slightly different:

I am trying to predict credit card approvals using the relevant dataset from UCI ML Repo. The problem is that the target encodes the applications for credit cards as '+' for approved and '-' for rejected.

As there are a bit more rejected applications in the target, all scorers, estimators are treating the rejected class as positive while it should be otherwise. Because of this, my confusion matrix is all messed up because I think all True Positives and True Negatives, False Positives and False Negatives get inverted:

How can I specify the positive class manually?

Good afternoon ,

Assume we have the following dataset from UCI :

Can someone explain what the bolded portions of this code. I have read the documentation for pandas and sklearn and it is still a bit hard to wrap my mind around it. I am wanting to modify this for my own data and would like to understand this a bit more.

HTTP cookies violate the REST architectural style because they are independent of application state and they have no semantics, according to Roy Fielding’s doctoral dissertation Architectural Styles and the Design of Network-Based Software Architectures, § 6.3.4.2 ‘Cookies’:

An example of where an inappropriate extension has been made to the protocol to support features that contradict the desired properties of the generic interface is the introduction of site-wide state information in the form of HTTP cookies. Cookie interaction fails to match REST's model of application state, often resulting in confusion for the typical browser application.

Cookies also violate REST because they allow data to be passed without sufficiently identifying its semantics, thus becoming a concern for both security and privacy. The combination of cookies with the Referer [sic] header field makes it possible to track a user as they browse between sites.

So he suggests the following alternative:

As a result, cookie-based applications on the Web will never be reliable. The same functionality should have been accomplished via anonymous authentication and true client-side state. A state mechanism that involves preferences can be more efficiently implemented using judicious use of context-setting URI rather than cookies, where judicious means one URI per state rather than an unbounded number of URI due to the embedding of a user-id. Likewise, the use of cookies to identify a user-specific "shopping basket" within a server-side database could be more efficiently implemented by defining the semantics of shopping items within the hypermedia data formats, allowing the user agent to select and store those items within their own client-side shopping basket, complete with a URI to be used for check-out when the client is ready to purchase.

My understanding of his user preference example is the following. Let’s say that a website allows its users to choose between a light theme (the default) and a dark theme in a preference page at URI /preferences (like Stack Overflow). When a user chooses the dark theme, he should be redirected to the URI /preferences?theme=dark whose HTML representation will be the same as the HTML representation of the URI /preferences, except that it will be now in dark mode and the query ?theme=dark will be appended to all the embedded hyperlinks. That way, if the user selects for instance the embedded hyperlink to the home page at URI /home?theme=dark (not /home), then the HTML representation of the home page will also be in dark mode and the query ?theme=dark will also be appended to all its embedded hyperlinks. To revert to the light theme, then the user selects the embedded hyperlink to the preference page at URI /preferences?theme=dark, chooses the light theme in the preference page and should be redirected to the URI /preferences whose HTML representation will be the same as the HTML representation of the URI /preferences?theme=dark, except that it will be now in light mode and the query ?theme=dark will be removed from all the embedded hyperlinks. Is it what Roy Fielding meant?

Likewise for his shopping cart example, when the user adds a product i to cart, he should be redirected to a URI with a query ?product-{i}={product-i}&quantity-{i}={quantity-i} whose HTML representation will have that query appended to all its embedded hyperlinks. That way, when the user selects the check out hyperlink /checkout?product-1={product-1}&quantity-1={quantity-1}&…&product-n={product-n}&quantity-n={quantity-n}, the content of the shopping cart is sent to the website. Is it what Roy Fielding meant?

I'm working a beginner tutorial on this dataset here:

http://archive.ics.uci.edu/ml/machine-learning-databases/undocumented/connectionist-bench/sonar/sonar.all-data

I've loaded it like so:

Because VSC says unresolved import 'scipy.ndimage' for from scipy.ndimage import interpolation as inter So I found the binary package for Windows at the bottom of https://scipy.org/install.html. I was able to

1. successfully install the required Windows VC++ buildtool, reboot
2. download the ndimage-1.3.1.tar.gz from above
3. python setup.py install gave me following error