jaccard | make calculating the Jaccard Coefficient Index
kandi X-RAY | jaccard Summary
kandi X-RAY | jaccard Summary
The [Jaccard Coefficient Index][1] is a measure of how similar two sets are. This library makes calculating the coefficient very easy, and provides useful helpers.
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QUESTION
I a trying to import training.txt data as follows.
...ANSWER
Answered 2021-May-17 at 17:59I didn't understand what you have tried to when you passed the variable training to the function.
But when you open a file you need to do it like that:
QUESTION
To calculate the distance between two sets of words I am using the jaccard distance:
...ANSWER
Answered 2021-May-04 at 17:37The most common distance measure between two sets (more generally, multi-sets) is the cosine distance (which is the angle) between the vector representations of the multi-sets.
Now let's see how you can represent a multi-set as a vector.
The first step is to representing each set as a bag if its members, e.g.
X = {a, b, a, c} ==> (a:2) (b:1) (c:1) Y = {d, b, a, d} ==> (a:1) (b:1) (d:2)
Each set is thus represented as a sparse vector of membership weights of the union set of all the members. For instance, the universal set of members in the above example is {a, b, c, d}, and the implicit weights of d and c in X and Y are 0.
With this sparse representation, which is convenient to store as a hashmap, you could then compute the cosine distance which is the arccos (inverse cosine) of the cosine similarity of the two vectors.
For two vectors x, y, the cosine similarity is computed as \sum_i x_i.y_i/(|x||y|), i.e. inner product of x and y divided by the product of the lengths of x and y.
In our example, the numerator is computed as 2x1 (product of the weight of member a in X and Y) + 1x1 + 1x0 + 2x0 = 3.
The length of x is sqrt(2x2+ 1x1 + 1x1) = sqrt(6), and it is easy to see that the length of y is also sqrt(6).
Hence cosine-distance = 3/(sqrt(6)*sqrt(6)) = 1/2, or in other words the angle between the vectors is 60 degrees.
Note: It is more common to omit the arccos operation and directly use the cosine similarity as a similarity (inverse distance) measure between multi-sets (represented as vectors).
QUESTION
I have a dataframe that looks like the following, but with many rows:
...ANSWER
Answered 2021-Apr-28 at 14:17Do you want this?
QUESTION
I have a dataframe that looks like the following, but with many rows:
...ANSWER
Answered 2021-Apr-28 at 11:34IIUC you just need to iterate over the unique values in the intent column and then use loc to grab just the rows that correspond to that. If you have more than two rows you will still need to use combinations to get the unique combinations between similar intents.
QUESTION
I am new to R and in need of advice how to subset a dataframe based on another dataframes data, so that they match, looking at number of rows and columns.
My overall goal is to perform a Mantel test between different versions of a test suite.
To do so, I have to compare the subset of the test cases that exist in Version 1 and Version 2, since in Version 2 more test cases have been added, but for a Mantel test you need (preferably) two symmetrical Matrices.
How my matrices look (small examples, they can have up to 4 million fields):
ANSWER
Answered 2021-Apr-11 at 18:36Here is a way to compare two symmetrical matrices (distance or correlation) and extract the rows/columns that are found in both. First we need some reproducible data:
QUESTION
I'm using GridSearchCV to hyperparameter tune my machine learning results:
ANSWER
Answered 2021-Apr-15 at 23:07Help on function make_scorer in module sklearn.metrics._scorer:
QUESTION
I want to get the Jaccard Similarity between my dataframe and the base. The issue is I need it for 500+ rows and I either get the error message: "too many values to unpack", 'Series' object has no attribute 'iterrows' or the functions compares the base witht the dataframe as a whole.
Alternative A:
...ANSWER
Answered 2021-Apr-14 at 13:57Try this - I'll add the explanation later need some work to do.
QUESTION
Before reading this I am extremely new to coding so many things I am going to ask are cringe.
I am using http://www.d2l.ai/chapter_recommender-systems/movielens.html and trying to use that dataset to grow my coding skills. I am coding in Python's Spyder.
What I was wondering was what if I was the CEO and wanted to know what the top 15 movies were by Name and Ratings given by users. This is simple enough for an intermediate coder but mind you I am the lowest a beginner can be. The code I have used so far is copy paste what they have done on that link in order to upload the file into Python.
My Mindset: I believe my next steps would be to create a DataFrame using Pandas and somehow use a value count. I am searching things up online and its throwing a bunch of info at me like Jaccard Similarities and Distances. I don't know if this type of question requires such a setup.
Any Help would be loved and if you do respond I may ask more questions out of curiosity.
...ANSWER
Answered 2021-Apr-05 at 06:02Assume you have downloaded ml-100k.zip and store it somewhere.
QUESTION
My code takes an eternity to compute jaccard similarity. It is an .csv file with 100000 in it. I have already created indexes on 2 basic Nodes (id+ value) I have already use the Jaccard algorithm in Playground but it also takes an eternity to run.
...ANSWER
Answered 2021-Mar-31 at 13:36The first two lines syntax of your query is not correct. You should run it like this:
QUESTION
My goal is to measure similarities between the rows of a dataframe and a list of words. My code looks like this:
...ANSWER
Answered 2021-Mar-17 at 18:01The result is right. See
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Install jaccard
On a UNIX-like operating system, using your system’s package manager is easiest. However, the packaged Ruby version may not be the newest one. There is also an installer for Windows. Managers help you to switch between multiple Ruby versions on your system. Installers can be used to install a specific or multiple Ruby versions. Please refer ruby-lang.org for more information.
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