I need to identify the sentiments for particular students with particular subjects in the form of:
st_id name subject 1st_Sem 2nd_sem 3rd_Sem 4th_Sem sentiment/output
1894 John English 88 90 64 58 Positive
1894 John Maths 64 30 23 31 Negative
Is there any method in machine learning to identify the sentiment using marksheet
Related
I have several multiple linear regressions to carry out, I am wondering if there is a VBA solution for getting the VIF of regression outputs for different equations.
My current data format:
i=1
Year DependantVariable Variable2 Variable3 Variable4 Variable5 ....
2009 100 10 20 -
2010 110 15 25 -
2011 115 20 30 -
2012 125 25 35 -
2013 130 25 40 -
I have the above table, with the value of i determining the value of the variables (essentially, different regression input tables in place for every value of i)
I am looking for a VBA that will check every value of i (stored in a column), calculate the VIF for every value of i and output something like below
ivalue variable1VIF variable2VIF ...
1 1.1 1.3
2 1.2 10.1
I have a CSV that contains some production data. When loaded into Excels power query it has a structure similar to this (material batches may contain remainders of old material batches as recycling material):
Mat_Batch Date Recyc_Batch RawMaterial1 RawMaterial2 RawMaterial3 Amount1 Amount2 Amount3
123 01.11.2019 Fe Cr Ni 70 19 11
234 01.12.2019 Fe Cr Ni 71 18 11
345 01.02.2020 123 Fe Cr Ni 72 17 9
456 01.01.2020 234 Fe Cr Ni 70 19 11
567 01.02.2020 Fe Cr Ni 72 16 10
678 01.01.2020 456 Fe Cr Ni 70 19 11
Another CSV has the following content (it simply links a production batch to a material batch; production batches may contain more than one material batch):
Batch Mat_Batch
abc 456
abc 567
bcd 345
Now I would like to use power query m to evaluate which material batches exactly were used to produce a part batch. E.g. batch "abc" was made from 456 + 567 + 234 (as recycling material in 456).
As a first step, I filter the production batch table by a specific batch and join both tables via the resulting Mat_Batch column. As a second iteration I seperate the Recyc_Batch column from the matched material batches and do a second join with a copy of my material batch table to gain all additional recycling materials that where used. But how could I do so "infinite" times? The way I'm doing it I have to create additional queries for each iteration but I need a way to automatically repeat those joining steps until there is no more additional recycling material used.
here is a Query (Result) you can use (if I understood correct)
let
Quelle = Table.NestedJoin(tbl_Material, {"Mat_Batch"}, tbl_Production, {"Mat_Batch"}, "tbl_Production", JoinKind.LeftOuter),
Combine_Sources = Table.ExpandTableColumn(Quelle, "tbl_Production", {"Batch"}, {"Batch"}),
DeleteOtherColumns = Table.SelectColumns(Combine_Sources,{"Batch", "Mat_Batch", "Recyc_Batch"}),
UnpivotOtherColumns = Table.UnpivotOtherColumns(DeleteOtherColumns, {"Batch"}, "Attribut", "Wert"),
FilterRows = Table.SelectRows(UnpivotOtherColumns, each ([Batch] <> null)),
SortRows = Table.Sort(FilterRows,{{"Batch", Order.Ascending}})
in
SortRows
The result looks like that
Best regards Chris
I am currently working on a decision support system for Licensure Examination Performance using Python but I stumbled with this problem. I want to determine which AREA should an examinee should concentrate on to be able to pass or at least get a Rating of 75.
Suppose I have the following dataframe in Python
Age Sex_M HS_GWA Col_GWA Major Passed_P Rating
21 1 85 90 1 1 85
23 0 87 88 3 1 75
19 0 91 92 2 1 77
20 0 86 85 0 1 80
20 1 76 86 1 0 65
22 1 88 75 2 0 70
I have SUCCESSFULLY implemented the classification (when the target is Passed_P) and regression (target variable is Rating) algorithms of SKLearn in creating prediction models and used them for prediction.
THE CHALLENGE:
What if HS_GWA is now the TARGET variable while Rating becomes constant at 75 and become part of the independent variables. How can we use the independent variables to determine/forecast the minimum value of the DEPENDENT variable?
What if HS_GWA is now the TARGET variable while Passed_P becomes constant at 1 and become part of the independent variables. How can we use the independent variables to determine/forecast the minimum value of the DEPENDENT variable?
I'm trying to make a cohort in Excel Pivot with a dataset having:
aggregated number of monthly sign ups (month by month), aggregated number user of completed next step, number of months between sign up and the next action taken.
What I can't figure out when i do the pivot to have the cohort, is what to put into the value field in the pivot? Normally I would take the Customer IDs as value, but since I only have the data on aggregated monthly level I'm not sure if i put the number of sign ups or the number of next step completed?
Also how do I get the sum of each cohort so i can calculated the retention rate?
I hope this make sense.
Signup month Action completed month Months between sign up and action completed signups conversion to Action completed
Jan-17 Sep-18 20 95 71
Jan-17 Jan-18 12 95 77
Jan-17 Jun-18 17 96 72
Jan-17 Jan-18 12 92 78
Jan-17 Dec-18 23 91 78
Jan-17 Jul-18 18 100 73
Jan-17 Oct-18 21 92 79
Jan-17 Feb-18 13 95 70
Jan-17 Jan-18 12 91 79
Jan-17 May-18 16 93 71
Jan-17 Jun-18 17 95 72
Is this what you are looking to achieve?
REVISION #1
This layout shows the total number of signups, by the month in which the signup occurred, distributed by the number of months btwn the signup and action completed. The action completed month may be omitted and will still achieve the same result; it is there FYI only.
REVISION #2
This is an example of the average months between the signup and action. Is this what you are looking for?
I have a DAX formula for my Powerpivot I cannot get to solve and was hoping for help.
I have two pivot tables connected already
Showing a cohort of actions taken within Month 1,….X on the sign up month
Total Sign Ups on monthly basis
I have tried to attached the sheet here but somehow I cant so I have add a screenshot of the sheet.1
What I have so far is:
=DIVIDE(
SUM(Range[conversion to KYC completed]),
SUM('Range 1'[Sum of signups]))
But this does not give me what I want as I think I’m missing the monthly grouping somehow.
Question 1:
What I want is to get the share of actions completed within 1,...,X months out of the total sign up that given month (e.g. Jan) (so the data from Table 2)
Question 2:
In best case I would also like to show total sign ups in the beginning of the cohort to make the cohort easier to understand, so having the monthly total sign up (which the cohort is calculated based on). But now I cannot get just the totals month by month. Is there anyways just to add in a monthly total column in the pivot without applying these number as a value across all columns?
Something like this is the ultimate outcome for me 2
UPDATED WITH SAMPLE DATA
Signup month, KYC completed month, Age by month, signups, conversion to KYC completed
Jan-17 Jul-18 18 97 75
Jan-17 Jul-18 18 99 79
Jan-17 Dec-18 23 95 80
Feb-17 May-18 15 99 74
Feb-17 Jul-18 17 90 75
Feb-17 Jul-18 17 95 76
Feb-17 Aug-18 18 92 71
Mar-17 May-18 14 94 73
Apr-17 Jul-18 15 93 75
May-17 Sep-18 16 94 70
May-17 Oct-18 17 98 72
Jun-17 May-18 11 95 79
Jul-17 Oct-18 15 97 74
Jul-17 Jul-18 12 94 78
Aug-17 Sep-18 13 96 74
Sep-17 Nov-18 14 95 80
Sep-17 Oct-18 13 94 79
DESIRED OUTCOME
The % for Month 1....X is calculated KYC Completed / Monthly Sign up
OUTPUT WITH THIS CODE
=VAR SignUpMonth = IF(HASONEVALUE('Range 1'[Row Labels]), BLANK())
RETURN
DIVIDE(CALCULATE(SUM([conversion to KYC completed])),
CALCULATE(SUM('Range 1'[Sum of signups]),
FILTER(ALL(Range), Range[Signup month (Month Index)] = SignUpMonth)))
[
Thanks for the sample data Franzi. Still not too clear what you're asking for, but perhaps this will help a little.
Signed Up to Signed In Ratio =
VAR SignUpMonth = SELECTEDVALUE(Table1[Signup month], BLANK())
RETURN
DIVIDE(CALCULATE(SUM([conversion to KYC completed])),
CALCULATE(SUM(Table1[ signups]),
FILTER(ALL(Table1), Table1[Signup month] = SignUpMonth)))
So. Let's break it down.
If I understand correct, you want to see the cross section of number of signins for a given month ( x axis ) signup combo ( y axis ) and divide that number by the total signups ( y axis ) per signup month.
number of signins for a given month ( x axis ) signup combo ( y axis ):
CALCULATE(SUM([conversion to KYC completed]))
TOTAL signups ( y axis ) per signup month
CALCULATE(SUM(Table1[ signups]),
FILTER(ALL(Table1), Table1[Signup month] = SignUpMonth))