Questions tagged [time]
The time tag has no usage guidance.
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I have these two questions in my assignment
Q: Part (a)Suppose we have a sequential problem of size n that needs n3 running time. Using p processors to parallelize the problem will not necessarily make the running time = n3/p. Please explain ...
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Finding the delayed effect of a change in input
I am trying to figure out the delay between changing the speed of a pump that pumps a modifier into a process and the change in Amps drawn by an extruder at the end of the process. The amps drawn are ...
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parallel work on KNN in python
I have a question, related to parallel work on python
How I can use Processers =1,2,3... on k nearest neighbor algorithm when K=1, 2, 3,.. to find the change in time spent, speedup, and efficiency.
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Handling date and time fields for classification task
I'm working on a classification task(The dataset is 400,000 rows and 30 columns) and one of my features was date-time. I've extracted the month, day of the week, and hour from the dataset (year is a ...
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Add timestamp as a feature to model
I am working with time-series data and am interested in adding time-stamp data (as a feature) into the (DNN) model. From the things I have read online so far, my only option is to come up with my own ...
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Setting Time and Date Format in Python
I have a dataset with a time column and a separate date column in .xlsx format.
time column has values in the below format:
12:32:21.499145197
12:32:21.499145197
date column has values in the below ...
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Potential models/methods to predict walking times in postal center
I have a dataset containing the walking times it takes to walk from one postal bin to another postal bin in a mail distribution center. The features I have, include the total mail workers on the floor ...
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Yahoo Finance Widget not in Time Series in Orange 3.30
When I add in Time Series version 0.3.12 in Orange version 3.30 "last version" the Yahoo Finance widget is not included. How do I add in the Yahoo Finance widget?
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I want to apply Time Series Clustering to time series data consisting on: Level & Growth, but I have only found algorithms for one series
Is there any implementation of Time Series Clustering which allows me to segment using two or more series of the same phenomenon both as input for the algorithm?
Suppose I have $A_{i,t}=X_{i,t}$ and $...
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Deep Learning with Time Series Data (containing Log Returns)
I am curious about how I would begin to approach this problem. I am working with a time series multi-indexed data frame (consisting of precomputed log returns) of various stocks. In this dataframe, ...
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Which is meant by +/-9.2e18 years in timespan?
I was able to convert the 9.2e18 AD to a date, but I am confused about the exact date. Which date is 9.2e18 AD and and 9.2e18 BC?
Time span (absolute) - [9.2e18 BC, 9.2e18 AD] i.e +/- 9.2e18 years
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Survival analysis to estimate kanban tasks completion times
I am working on a problem to estimate task completion time in kanban (project management tool).
While doing EDA, I looked at tasks that are either done or cancelled. In this case, I defined the ...
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What is best practice to feature engineer from prior event counts?
Say for example I am building a model to predict a customer churn event from Spotify, with my target being whether a customer churns in the next 90 days.
One feature I might expect could be predictive ...
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Modeling count data with time-dependent rate
For processes of discrete events occurring in continuous time with time-independent rate, we can use count models like Poisson or Negative Binomial. For discrete events that can occur once per sample ...
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LSTM for time series forcasting
I manipulate the time series using the different structures of the neural networks in order to make a prediction, and I wonder if there is a way to choose the parameters of the networks intelligently? ...
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Date and time extraction from Excel file in Python or Pandas
I have an Excel file with a column that contain both date and time in a single cells as follows:
2020-07-10T13:32:01+00:00
I'm wondering how to extract this cell, split date and time (that are ...
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Appropriate Machine Learning algorithm for modeling clustered time-varying binary outcome
I'll just dive right in. I have a decent-size (100K observations) dataset of time-varying continuous and categorical predictors. Categorical predictors, actually, usually do not change, however, ...
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Get the average time between first and 2nd call (postgresql)
I have the following data in table where I want to calculate the average time between 1st and 2nd call.
I know how to get the average, but I have a though time to figure out how to subtract the 2nd ...
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Help improving my "read_excel" execution time in python. My code reads slowly
My first question here so please bare with me.
I'm trying to feed my neural network with training data read in from an excel file. It works perfectly fine when i have less than 50 rows in the sheet. ...
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Standard(s) for data representing measurement times with their interval of validity?
Is there a standard for representing the time interval of a measurement?
Any actual measurement is made at a point in time with, perhaps, an interval over which it is considered valid. For example, ...
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Classification with feature not available at time of model creation
I have problem statement to predict the probability of solving a task depending on multiple features for e.g. when the task was created, the time needed to work on a task, etc Please find a dummy ...
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In survival analysis, which is the correct way to introduce a variable which changes the survival rate but occurs at different times?
I am making a survival analysis with a cox regression with proportional hazards, we want to analyze wheter the introduction of a phenomenon influences the time until the death of an individual.
A ...
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'list' object has no attribute 'values' when we are using append in python
Here I have a dataset with three inputs. Here I generated y value using append. After the append I got the output like this:
y.append(rec.iloc[0]['y'])
Then I ...
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Linear correlation and XGboost regression for time series
I am working with sales time-series data, I have a history of 9 years of monthly data. I am trying to forecast sales for the next 12 months. I am using XGboost regression to build multivariate time ...
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