I have been working on a calculated Nested If Statement in SharePoint that does not work, if anyone if familiar with SharePoint syntax than please help me, here is the statement, I keep getting errors.
=IF(OR([Is 100% of the Sellers work being performed in an office area, performing administration services (i.e. data entry, developing drawing, monitoring phone calls etc.)?]) = "Yes","Low Risk","High Risk",[Is the Contractor/Seller 100% of the time escorted by a XX Employee or XX Representative for consulting or observation only services (i.e. looking but not touching)?] = "Yes","Low Risk","High Risk")
I assume the long sentence is only the field name, so the formula will be converted to the one below
=IF(OR([A]) = "Yes","Low Risk","High Risk",[B] = "Yes","Low Risk","High Risk")
The issue seems to be the or part as the syntax of OR function is
OR(logical1,logical2,...),Returns Yes if any argument is TRUE; returns
No if all arguments are FALSE.
I assume you want to make the field work like Either A or B field value is "Yes", the outcome is Low Risk, or it will be High Risk.
So the formula shall be like =IF(OR([A]= "Yes",[B] = "Yes"),"Low Risk","High Risk")
Replace the actual name with A, B, the formula finally will be
=IF(OR([Is 100% of the Sellers work being performed in an office area, performing administration services (i.e. data entry, developing drawing, monitoring phone calls etc.)?]= "Yes",[Is the Contractor/Seller 100% of the time escorted by a XX Employee or XX Representative for consulting or observation only services (i.e. looking but not touching)?] = "Yes"),"Low Risk","High Risk")
Related
I am trying to predict match winner based on the historical data set as shown below,
The data set comprises of IPL seasons and Team_Name_id vs Opponent Team are the team names in IPL. I have set the match id as Row id and created the model. When running realtime testing, the result is not as expected (shown below)
Target is set as Match_winner_id.
Am I missing any configurations? Please help
The model is working perfectly correctly. There's just two problems:
Your input data is not very good
There's no way for the model to know that only one of those two teams should win
Data Quality
A predictive model needs good quality input data on which to reverse-engineer a model that explains a given result. This input data should contain information that can be used to predict a result given a different set of input data.
For example, when predicting house prices, it would need to know the suburb (category), number of bedrooms/bathrooms/parking spaces, age of the building and selling price. It could then predict the selling price for other houses with a slightly different mix of variables.
However, based on your screenshot, you are giving the following information (and probably more) on which to make your prediction:
Teams: Not great, because you are separating Column C and Column D. The model will assume they are unrelated information. It doesn't realise that those two values could be swapped.
Match date: Useless information unless the outcome varies in proportion to time (eg a team continually gets better)
Season: As with Match Date, this is probably useless because you're always predicting the future -- you won't be predicting for a past season
Venue: Only relevant if a particular team always wins at a given venue
Toss Decision: Would this really influence the outcome? Also, it's only known once the game begins, so not great for predicting a future game.
Win Type: You won't know the win type until a game is over, so it's not suitable for predicting a future game.
Score: Again, not known until the actual game, so no good for future predictions.
Man of the Match: Not known for future games.
Umpire: How does an umpire influence the result of a game?
City: Yes, given that home teams often have an advantage.
You have provided very little information that could be used to predict a future game. There is really only the teams and the venue. Everything else is either part of the game itself or irrelevant.
Picking only one of the two teams
When the ML model looks at your data and tries to make a prediction, it will look at all the data you have provided. For example, it might notice that for a given venue and season, Team 8 has a higher propensity to win. Therefore, given that venue and season, it will favour a win by Team 8. The model has no concept that the only possible outcome is one of the two teams given in columns C and D.
You are predicting for two given teams and you are listing the teams in either Column C or Column D and this makes no sense -- the result is the same if you swapped the teams between columns, but the model has no concept of this. Also, information about Team 1 vs Team 2 is totally irrelevant for Team 3 vs Team 4.
What you should do is create one dataset per team, listing all their matches, plus a column that shows the outcome -- either a boolean (Win/Lose) or a value that represents the number of runs by which they won (where negative is a loss). You would then ask them model to predict the result for that team, given the input data, which would be win/lose or a points above/below the other team.
But at the core, I think that your input data doesn't have enough rich content to be able to make a sensible prediction. Just ask yourself: "What data would I like to know if I were to guess which team would win?" It would probably be past results, weather conditions, which players were on each team, how many matches they played in the last week, etc. None of this information is being provided as input on each line of your input data.
I have values for postage, pricing and postage service (only if). I have two choices for postage service (express and eco), price depends on a weight, but service depends on a price (fast service for items over £5, eco - under).
Service: if product price(A2)
<5=eco; >5=express
Service price(C2) by weight(B2):
<=1000gr= £2 eco or £3 express
1001-1250gr= £5 eco or £6 express
1251-5000gr=£9 eco or £11 express
Cells A2 and B2 always display a value, need a formula for C2 to display the price of service calculated by weight, but if item over £5 must display express service price if less - eco.
I have tried:
>IF(AND(OR(B2<=1000),A2<5),2,IF(AND(OR(B2>1000,B2<=1250),A2<5),5,IF(AND(OR(B2>1250,B2<=5000),A2<5),9)))
>IF(AND(OR(B2<=1000),A2<5),2)+IF(AND(OR(B2>=1001,B2<=1250),A2<5),5)+IF(AND(OR(B2>2000),A2<5),9)
Didn't start adding A2>5, because nothing works anyway! Tried many more, but no luck.
Would appreciate any help because stuck and ran out of options :(
Thanks!
There are a couple of ways to accomplish this. The preferred method is to build a small cross-reference table for your surcharges and use the VLOOKUP function to return the values.
However, this question was about hard-coded values in a conditional statement, so I will address that with a LOOKUP function and arrayed constants.
The standard formula in C2 is,
=LOOKUP(B2,{0,1001,1251},{2,5,9})+SIGN(A2)*LOOKUP(B2,{0,1001,1251},{1,1,2})
Fill down as necessary.
In the following image, custom number formats were used on columns A and B ([Color9]\Exp\r\e\s\s - [$£-809]#,##0.00;;[Color10]\Eco - [$£-809]#,##0.00; and 0\g\r_)). Weights >5000 in column B trigger a conditional formatting in column C that displays too heavy.
I'm working with our IT group to develop an optimizer for logistics operations. The basic design is that it will look at shipments, run a search for additional shipments originating with in XX miles of the previous shipments destination, and link them together in a loop. It will continue to do this until it hits a user defined set of shipment legs where the loop ends at or close to 1st shipment origin.
The issue we are facing is that the materials we ship are chemicals, which can have interactions if placed in a tank that contained XX chemical before it. The obvious solution is to use a different tank or wash it out, but we also need it to compute solutions prior to that.
My problem is, currently, there is no way on the market to do that prior product optimization.
The question is: Is there some kind of logic table function I can write that will allow the optimizer to see an element in the data set (say, Product Family of 1) that will pull from a product database containing predefined product families (i.e. PF 1 = Chemicals A1-B7, PF 2 = Chemical B8-J8, etc.) and then ping off of a logic table that defines a do not ship with list (i.e. PF 1 cannot ship if PF 2 was on the previous leg.
We’re using JCo 3.0 to connect to RFCs and read data from SAP R/3. We use one RFC RFC_READ_TABLE often and use a second custom RFC to read employee information. My questions revolve around a third RFC RSAQ_REMOTE_QUERY_CALL. I'm calling an ad-hoc query I built in SAP using this RFC but I’m not getting the expected results. The main problem is that it appears that SAP is ignoring one of my selection criteria and using what was saved in SAP when I originally built it. The date criterion stored in my ad-hoc is 6/23/2013. If I pass in 6/28/2013 from JCo, I get the same results as if I had passed 6/23/2013 from JCo.
We have built several ad-hoc queries whose only criteria is a personnel number and call them successfully using RFC RSAQ_REMOTE_QUERY_CALL.
Background on my ad-hoc query: reporting period of today, joining together four aspects of an employee’s information: their latest action (hire, rehire, etc.), organization (e.g. company), pay (e.g. pay scale level) and communication (e.g. email). The query will run every workday.
Here are my questions:
My ad-hoc has three selection criteria. The first two are simple strings. The third is a date. The date will vary each time the query runs. We are referencing the first criteria using SP$00001, the second with SP$00002 and the third with SP$00003. The order of the criteria changes from the ad-hoc to SQ01 (what was SP$00001 in the ad-hoc is now SP$00003). Shouldn’t we reference them in the order defined in the ad-hoc (e.g. SP$00001)?
The two simple string selections are using OPTION “EQ”. The date criteria is using OPTION GT (greater than). Is “GT” correct?
We have some limited accessibility to SAP. Is there a way to see which SP$ parameters are mapped to which criteria?
If my ad-hoc was saved with five criteria but four of them never change when I call the ad-hoc from JCo, do I just need to set the value of the one or do I need to set the other four as well?
Do I have to call this ad-hoc using a variant (function.getImportParameterList().setValue(“VARIANT”, “VARIANT_NAME”))?
Does the Reporting Period have an impact on the date criteria? I have tried changing the Reporting Period to be PNPBEGDA = today and PNPENDDA = today and noticed no change.
Is there a way in SAP to get a “declaration” of your ad-hoc (name, inputs, outputs, criteria)? I have looked at JCoFunction.toXml() and JCoFunctionTemplate. These are good if you want to see something at runtime before it goes to SAP, but I’m looking for something I can use on the JCo end to help me write Java code that matches the ad-hoc.
I have looked at length on the web for answers to my questions and have not found anything that is useful. If there is anything which would help me, please let me know.
Thanks,
LM
Since I don't know much about SQnn, I won't be able to answer all of your questions...
I don't know, sorry.
It should be, at least it's the usual operator for greater than.
Yes - set an external breakpoint right inside the function module and trace its execution while performing the RFC call. Warning: At least basic ABAP knowledge required.
I don't know, sorry.
I don't know either, sorry.
That would depend on the query, I suspect...
JCo won't be able to help you out there - it doesn't know about queries, it only knows function modules. There might be other RSAQ_* function modules to get that information though.
I played with setting up a variant in SQ01 for my query. I added some settings in the variant that solved my problem and answered several of my questions in my post. The main thing I did was add a dynamically calculated date as part of my criteria. Here's how:
1. In SQ01, access menu "Go To" -> "Maintain Variants".
2. Choose your variant and in subobjects, choose "Attributes" and click "Change".
3. In the displayed list, find your date criterion.
4. Choose "D" in Selection Variable, choose a comparison option (mine was GT for greater than), and a "Name of a Variable" (really, this is the type of dynamic date calculation you need).
5. Go back to the Subobjects panel, choose "Values" and click "Change".
6. Enter any other criteria you need in the "Program selections" section.
7. Save the variant.
By doing this, I don't need to pass anything into the query from JCo. Also, SAP will automatically update the date criteria you entered in step #4 above.
So to to answer my questions from my original post:
1 and 4. It doesn't matter because I'm no longer passing anything in from JCo.
2. "GT" is Greater Than.
3 and 7. If anyone knows, I'd really like to find out.
5. Use the name you as it is in SAP (step #2 above).
6. I still don't know, but it's not holding me up.
I'm posting this in case anyone out there needs this type of information. Thanks to Esti and vwegert for helping me out.
Having implemented an algorithm to recommend products with some success, I'm now looking at ways to calculate the initial input data for this algorithm.
My objective is to calculate a score for each product that a user has some sort of history with.
The data I am currently collecting:
User order history
Product pageview history for both anonymous and registered users
All of this data is timestamped.
What I'm looking for
There are a couple of things I'm looking for suggestions on, and ideally this question should be treated more for discussion rather than aiming for a single 'right' answer.
Any additional data I can collect for a user that can directly imply an interest in a product
Algorithms/equations for turning this data into scores for each product
What I'm NOT looking for
Just to avoid this question being derailed with the wrong kind of answers, here is what I'm doing once I have this data for each user:
Generating a number of user clusters (21 at the moment) using the k-means clustering algorithm, using the pearsons coefficient for the distance score
For each user (on demand) calculating their a graph of similar users by looking for their most and least similar users within their cluster, and repeating for an arbitrary depth.
Calculating a score for each product based on the preferences of other users within the user's graph
Sorting the scores to return a list of recommendations
Basically, I'm not looking for ideas on what to do once I have the input data (I may need further help with that later, but it's not the point of this question), just for ideas on how to generate this input data in the first place
Here's a haymaker of a response:
time spent looking at a product
semantic interpretation of comments left about the product
make a discussion page about a product, brand, or product category and semantically interpret the comments
if they Shared a product page (email, del.icio.us, etc.)
browser (mobile might make them spend less time on the page vis-à-vis laptop while indicating great interest) and connection speed (affects amt. of time spent on the page)
facebook profile similarity
heatmap data (e.g. à la kissmetrics)
What kind of products are you selling? That might help us answer you better. (Since this is an old question, I am addressing both #Andrew Ingram and anyone else who has the same question and found this thread through search.)
You can allow users to explicitly state their preferences, the way netflix allows users to assign stars.
You can assign a positive numeric value for all the stuff they bought, since you say you do have their purchase history. Assign zero for stuff they didn't buy
You could do some sort of weighted value for stuff they bought, adjusted for what's popular. (if nearly everybody bought a product, it doesn't tell you much about a person that they also bought it) See "term frequency–inverse document frequency"
You could also assign some lesser numeric value for items that users looked at but did not buy.