rfm | FileMaker to Ruby adapter
kandi X-RAY | rfm Summary
kandi X-RAY | rfm Summary
This library is no longer maintained. It is known to work up to Filemaker version 14. Beyond that there is no guarantee. There is currently a maintained fork that goes under a different gem name here:
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Top functions reviewed by kandi - BETA
- Expands the given arguments into a hash .
- Find the record by id
- Fetch the raw data from a URL
- Parse the HTTP request .
- Parses all fields related to the server
- Read a single attribute from the attributes hash
- convert date format
- Builds a message .
- Find records by id
- Returns the port for the given port .
rfm Key Features
rfm Examples and Code Snippets
Community Discussions
Trending Discussions on rfm
QUESTION
I am building an RFM table in excel, and want to lookup against a score table I created. Using row 3 as an example in the pic below, when I use the vlookup true function which is supposed to return a close match from the recency rankings table the vlookup is pulling in a 5 in column F, instead of a 1. I am not looking to do an exact match as that is not how this analysis is structured.
Any thoughts on why the true statement in the vlookup is not returning correct values? Any thoughts on how to fix would be appreciated.
enter image description here
ANSWER
Answered 2021-May-19 at 06:14When you use TRUE as the final parameter in VLOOKUP (for "approximate match"), Excel (for whatever reason) stipulates that the corresponding values in the first column of the lookup range must be in ascending order. The prompt as you're typing the formula notes this
Therefore, re-order your lookup table and then the VLOOKUP values should populate as you expect them to
QUESTION
I have the following pandas Dataframe:
...ANSWER
Answered 2021-Apr-26 at 16:55- Prepare data:
QUESTION
I have a Dataframe with several column and below is first 3 columns in that dataframe:
...ANSWER
Answered 2021-Apr-26 at 15:37Create a dict for mapping -
QUESTION
I made a representation of a random forest tree in reprtree
but I have too much nodes I think:
The line I wrote : RFM = randomForest(Rating ~., data = training)
I would like to take off some variables which are not relevant, but everything I write does not work; I tried :
RFM = randomForest(Customer_type, Rating, cogs, data = training)
to have only those three variables but I still have an error.
Do you know how could I 'select' my variables in the dataframe without writing Rating ~.
formula? I tried to change ntree
but I still have too much nodes.
ANSWER
Answered 2021-Apr-16 at 09:30randomForest
accepts a formula object. Try :
QUESTION
I'm a newbie in R, I'm trying to predict a Customer Type (member or normal customer in the store) in relation to different variables (Gender, total spent, rating, ...) with 1000 customers information in my dataframe. I created an algorithm with a random forest but the accuracy is around 49% (OOB error rate). I tried to use Importance(RFM) in order to get higher accuracy by not including not relevant variables but I end up with around a 51% accuracy... Does it mean there is no connection between all the features or is there a way to tune it to get higher accuracy ? Thank you so much.
...ANSWER
Answered 2021-Apr-18 at 10:45Without your data or a reproducible example, it is hard to really improve your model. I can suggest to you some procedures and packages that can help you a lot in this kind of task.
Have a look at the caret
package, which is designed precisely for model tuning. The package is really well documented with lots of useful examples. Here I can show the general workflow to work with caret
:
QUESTION
I'm really new to R and I want to make a random forest. However I keep getting the same error-
Error in model.frame.default, lengths of variables differ.
I know this issue has been solved in another topic by constructing a formula from strings with as.
formula but I have really no idea how to do it. Can you help me please? Thank you.
ANSWER
Answered 2021-Apr-14 at 18:23Well what your error is, is that your independent variable is Rating
from the df
dataframe, but you selected data = training
. This means that your random forest should take data from 2 different dataframes, which isn't possible.
I guess that randomForest(Rating ~ Customer_type, data = training)
would work.
QUESTION
What I wanna do
I want to do RFM analytics for purchase data of a e-commerce site.
I processed the data into RFM format, so I want to rank every ID depending on the values of each column (Money, Recency and Frequency).
However, I got the error message as below.
...ANSWER
Answered 2021-Apr-13 at 06:15If working with scalars use and
instead &
with remove last level of MultiIndex
by MultiIndex.droplevel
.
So use:
QUESTION
I have a dataframe
as shown below. I want to group and return the count of Campeão
registers, so that I can have this scalar into a output text for users.
I'm using this code to display a table with each correspondent value
a = df['Macro RFM'].value_counts().reset_index()
st.dataframe(a)
How can I get the result for each class (Macro RFM
)? I mean, I want to output something like that:
st.write(f'We got {X} champions')
ANSWER
Answered 2021-Mar-24 at 16:13What about:
QUESTION
ANSWER
Answered 2021-Mar-22 at 16:08What about this:
QUESTION
I want to add color legend like this:
...ANSWER
Answered 2020-Nov-20 at 11:23Seaborn's scatterplot
would automatically create a legend. The hue=
tells which column to use for coloring, the palette=
parameter tells the colors to use (either a list or a colormap). For non-numeric data, hue_order=
can fix a certain ordering.
Here is an example with toy data:
Community Discussions, Code Snippets contain sources that include Stack Exchange Network
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Install rfm
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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