how to implement neural network on a small dataset for binary classification?
how to implement neural network from scratch on a small dataset for binary classification in matlab?
check this video about.
method for handling data structures where the first element is processed first and the newest element is processed last. Hi JimCreech,


It is possible to achieve a similar result in Dataiku by going through the following steps:


* run a [Window](https://knowledge.dataiku.com/latest/courses/visual-recipes/window.html) recipe using id as partitioning column, event as ordering column, and compute the lagdiff values on days
* run a [Prepare](https://knowledge.dataiku.com/latest/courses/basics/prepare-data/concept-prepare-recipe.html) recipe which will:
	+ run the assertions on the specific conditions you mentioned and create a dummy\_tmp column we'll reuse at the final step
	+ filter out the records where event == 01 (since we won't need it for the aggregation)
* run a [Groupby](https://knowledge.dataiku.com/latest/courses/basics/group-data/group-summary.html) recipe to aggregate at the id level and get the minimum of the dummy\_tmp column (which should be 1 if all conditions you described are verified, 0 otherwise).


You will find attached a sample DSS project with an example of implementation of those steps using the small example data mentioned in your post. If you are working on a regular basis with time series data, you may find this [tutorial](https://knowledge.dataiku.com/latest/courses/visual-recipes/window/window.html) on the Window recipe capabilities useful.


Hope this helps !


Best,


Harizo




[View solution in original post](/t5/General-Discussion/Using-Lag-and-Lead-in-Dataiku/m-p/19308#M1146) [@sensiblearts](/u/sensiblearts) has been working on a guide for libcluster setup (that will be put up on [powauth.com](http://powauth.com)). here’s a way to handle it: <https://github.com/pow-auth/pow_site/issues/10#issuecomment-533845299>

i’ve tested it locally with a k8s cluster, and it worked perfectly scaling up and down. if you push t… hi, @ricky007 
create table bill\_stag
(
s\_categry varchar2(20),
s\_billnum varchar2(20)
);

insert into bill values('1111','5647859541785');
watch out! you're using two different table names there.
you don't care which m\_billnum\_seq gets assigned to which new row, do you? (you shouldn't.) in that case, you can simplify the cross join approach that cormaco suggested like this:
insert into bill\_mast (m\_bill\_seqnum, m\_billnum, channel) -- always name the columns
with  all\_channels  as
(
 select 'mob' as channel  from dual  union all
 select 'atm'      from dual
)
select  seq\_num.nextval
, s.s\_billnum
, c.channel
from     bill\_stag    s
cross join all\_channels c
;
you don't need order by, so you don't need the ord column and you don't need so an extra sub-query. small biomarker = "hi!"

def cells = getdetectionobjects()

cells.each{

it.setname(biomarker)

}

all of the cells will now be named hi! this is a terrific question and i am glad you asked it.  as i am only in the beginning stages of planning to implement this here (it has not been a requirement yet, but will be soon), i can only add some preliminary thoughts to yours:

microsoft should bold, underline, highlight, and add 50 exclamation points to that statement about keeping queues to a minimum.  the performance hit is staggering, if your system has a high number of concurrent users.  you probably won't notice it in your dev or test environments if there aren't many simultaneous testers, however.

so in the spirit of getting the most protection from the fewest number of queues, i am asking some of the following questions:
* is it sufficient to classify ticket data along the lines of "sensitive, private, privileged" or some other such division, so that i could only create queues based on the sensitivity level of information, and not have to split it further by department/team/function/etc.?  this is a business question that will vary for everyone, of course.
* if the above is possible, i can add a classification enum to the tickets and develop a procedure for which should be selected, and base the queue on its value.  if it is not, or if my ticket category or support team already tells me what i need to know, then this is not even necessary.
* if data sensitivity is not a viable way to divide queues, then do i have certain support groups that need a queue, and all others would not belong to a queue?

in any scenario i have described or implied, this means that (most) teams can see each others' tickets.  this is not a problem for me in this environment, but might be for others.  as long as i wrap a queue around the most sensitive tickets, i do not mind if the rest are out in the open.

again, i have not proven these thoughts in production yet, but hopefully it helps to some degree. i optimize for local cases and have an so There are certainly other methods that can be used, but what you describe is simple and timeproven. It also happens to be what I (tend to) use when moving data between systems 🙂 It beats media and, if you don’t need real time replication of data, gets the job done.


Bruce Vining


May I suggest a one-step method, ObjectConnect using SAVRSTLIB or SAVRSTOBJ.


There is a little of prep work to do, like ,


* You need to install licensed program 5722SS1 option 22,
* Change network attributes to “Allow Anynet support” to *YES
* Create a host table entry on host system for target system with valid IP address with host name of targetsysname.SNA.IBM.COM
* Create an APPC controller on host and target systems using this


CRTCTLAPPC CTLD(XXXX) LINKTYPE(*ANYNW) RMTNETID(SYSTEMB) RMTCPNAME(ANYNET)TEXT(‘AnyNet connection to system SYSTEMB’)  

XXXX = the controller name  

RMTNETID = the remote systems name  

RMTCPNAME = the remote control point name


* Then finally create or modify the Remote Configuration list for QAPPNRMT:



```
CRTCFGL TYPE(*APPNRMT) TEXT('AnyNet TCP Connection list') <<ENTER>>
```

or



```
CHGCFGL TYPE(*APPNRMT) <<ENTER>>
```

REMOTE LOCATION= the target system name.  

REMOTE NET ID: APPN  

LOCAL LOCATION: The local systems name is found by issuing a DSPNETA.  

REMOTE CONTROL POINT: Is the same control point that was used when creating the controller.  

CONTROL POINT NET ID: APPN


If you need additional, please feel free to contact me.  

Karl sure, here you go:

import plotly.express as px

import pandas as pd

import numpy as np

from natsort import natsorted

df = pd.dataframe(dict(

value = np.random.rand(30),

bucket = ["[1-5)", "[10-15)", "[5-10)"]*10

))

px.violin(df, x="bucket", y="value", color="bucket",

category\_orde…