I want to find the similarity using cosine similarity operator on the structured dataset but I am not getting the desired result. Can someone guide me how to find the similarity using the Rapidminer?
Sample dataset:
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I am trying to analyze a dataset in WEKA with a nominal class. However, all the other attributes have both numeric and nominal values but the final class has nominal values. All algorithm options except very few are showing up? Can you please tell me why this is happening?
I have a Data Set of online product-reviews (without any grades/stars/etc.). To this data-set I applied the integrated PowerBI AI-Insights Text Analytics Sentiment Analysis model and got a a sentiment score for each review. Next, I transformed the score into textual discrete values: POSITIVE, NEGATIV and NEUTRAL.
The dataset is artificially created by me, so I know the polarity of each comment. Now I want to compare the predicted value to the actual value. I've done this by adding a new column that compares the actual value with the predicted value and displays "PREDICTED" if the correct value was predicted and "NOT PREDICTED" if the prediction was false (it doesn't matter if it is positive, negative or neutral). My goal is to calculate some model metrics so I can evaluate the capabilities of this PowerBI integrated model and to visualize the results. How can I do this? Is "accuracy" the first thing that I have to start with? If yes then how can I calculate and visualize a result like the "accuracy".
Thank you for all your answers in advance.
Yes, take accuracy in first consideration. If you find 70 or 80 percent above results are accurate, you can easily rely on the PowerBI AI-Insights Text Analytics Sentiment Analysis. You can then create your visuals for Sentiment data. But if there is 50-50 occurrence of predicted and not predicted result, you may go for 3rd party Sentiment analysis service like - Google, Alchemy.
I'm trying to find the median of a column based on two conditions. I thought using an ArrayFormula is best since there is no "medianifs"...I'm getting a result in my first cell but when I try to change the criteria in the cell beneath, you'll see I'm getting the exact same result, so I know something is wrong. Maybe the formula in the first cell isn't even the correct answer?
Here's my sheet.
I'm down in P94 and P95 trying to get the median values, you'll see the formulas that I've tried thus far.
Based on what you are attempting, I would use a filter to narrow down the criteria.
=MEDIAN(FILTER(N:N,F:F=O1,I:I=P1))
That way the data you are taking the median of is always the exact dataset needed.
The summarize command creates various scalars in Stata. For instance, one can store the mean or min/max values through gen mean=r(mean)afterwards.
It is also possible to get more sophisticated measures via the summarize varname, detailoption. Through this, one also obtains the median in form of the 50% percentile.
My goal is to store the median. Is there a corresponding scalar?
Where can I obtain information on stored scalars after standard operations like summarize? As far as I can see they are not listed in the Stata manuals.
After each command, one can find out where the results are saved through ereturn list or return list.
In the case of summarize varname, detail the median can be obtained through r(p50).
summarize varname, detail
return list
local var_median = r(p50)
The scalars stored by the summarize command are documented at the end of the output of help summarize and in the "Stored results" section of the Stata manual documentation for the summarize command found in the Stata Base Reference Manual PDF included with your Stata installation. In general, returned results for all commands are found in locations analogous to these.
I have a single continuous variable with highly skewed distribution. I have log transformed it for normalization. while creating a histogram of the variable with PROC UNIVARIATE (SAS 9.3), is there a way by which I can plot the transformed variable, but keep the values of original variable on x axis ?
if this topic has been already discussed then, I would really appreciate if someone can provide a link. Thank You.
You could use the SAS Graph Template Language (GTL) to do this. The documentation contains plenty of examples that you should be able to change and modify to your needs. The output from PROC UNIVARIATE is produced by the GTL so you should be able to generate something similar.
Take the output dataset from proc univariate and base the plot off that. You will need to reverse the transformations first.
Documentation for the GTL:
http://support.sas.com/documentation/cdl/en/grstatgraph/65377/HTML/default/viewer.htm#p1sxw5gidyzrygn1ibkzfmc5c93m.htm