icp | iterative closest point | Machine Learning library

I'm working on filtering a website's data and looking for keywords. The website uses a long JSON body and I only need to parse everything before a base64-encoded image. I cannot parse the JSON object regularly as the structure changes often and sometimes it's cut off.

Here is a snippet of code I'm parsing:

I am trying to plot pdp, ale and ICE plots for a regression Xgboost model in r built using the Xgboost library. I have tried this using the pdp library:

I am creating a framework to test a web app using Specflow and Nunit and I have run into an error that I previously did not have.

The error I get is: BoDi.ObjectContainerException: 'Interface cannot be resolved: OpenQA.Selenium.IWebDriver'

This originates in the base class when I try to resolve the _container into a IWebDriver.

I get no compile errors with this and the bug only shows up when the test is run.

BasePage.cs

I am frustrated because I'm a very Junior in React so I don't know if I made something wrong or not, because I really don't understand why, but part of the CSS don't apply to my code and I feel it's not normal...

This is my JS code:

I have a domain A.tk in the Cloudflare, and I have a server that cannot use the port 80 with domain A.top. The only way to visit A.top is A.top:61445, so I try to fetch('A.top:61445') in Cloudflare worker, and change the response when visiting A.tk. Everything is OK in the worker but not in the browser, where is the problem?Is it might cause of ICP?(I haven't get it)

Below is my controller

I've been working on this for hours and I can't seem to figure it out. I'm trying to compare two arrays of strings and using a third array to list the odd ones out. This is what I have:

I have 3 point clouds (cloud 0, cloud 1 and cloud 2), obtained in 3 different positions using a Terrestrial Laser Scanner. These clouds overlap between them, which means that there is a rigid 3D body transformation, T, which correctly registers one cloud on another. I have two of these transformations, T10, which moves cloud 1 to cloud 0; and T20, which moves cloud 2 to cloud 0 (cloud 0 was chosen as the global reference). The question is, how do I find the transformation that overlaps cloud 2 with cloud 1? I already found the rotation, but I can't find the translation vector. It's possible?

The rotation I found by multiplying the transformation T20 by the inverse of T10, because T10^(-1) = T01, therefore, T20*T01 = T21. When I apply this transformation to cloud 2 it rotates cloud 2 to cloud 1 correctly (both are in the same direction), but there is a shift between them, I don't understand why.

These transformations are just homogeneous matrices T (4x4) which are simply the junction of a rotation matrix R (3x3), and a translation vector t (3x1), right? Rotations can be composed. The fact that I found the rotation from cloud 2 to cloud 1 shows this. But why does this shift appear in translation?

In fact, I have several clouds, to register a cloud far from the origin, I need to accumulate several transformations through multiplications (for example: T50 = T54 * T43 * T32 * T21 * T10), the more I multiply the greater the difference in translation.

I would like to say that although the multiplication accumulates errors, they are very small, since the registration was done manually and refined by ICP. In fact, applying any of the transformations in pairs results in an almost perfect overlap, but accumulating them causes a huge deviation in translation. The rotation is so good that loop closure practically results in the identity matrix.

I have a data frame which contains the information of customer type. I used groupby to count the type of customer within each category using following command: