kaggle | Additional files for the Otto Group Challenge | Machine Learning library
kandi X-RAY | kaggle Summary
kandi X-RAY | kaggle Summary
For the Otto Group Product Classification Challenge, hosted by Kaggle, we have provided a dataset with 93 features for more than 200,000 products. The objective is to build a predictive model which is able to distinguish between our main product categories.
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Top functions reviewed by kandi - BETA
- Train the Random Forest classifier
- Load train data
- Calculate the log loss for the MCMC
- Make a submission file
- Load test data
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QUESTION
How do you calculate the model accuracy in RStudio for logistic regression. The dataset is from Kaggle.
...ANSWER
Answered 2021-Jun-15 at 21:39use the package ML metrics
QUESTION
Today i upgraded my account to Colab pro. Although it prints the ram as:
...ANSWER
Answered 2021-Jun-09 at 19:00Looking at your error, the 16 GB are referring to the graphics card, not the ram.
As far as I know, using colab-pro enables you to use a graphics card with up to 16GB of VRAM.
You can check the VRAM amount by running the following code.
QUESTION
I am running the following code against the dataset of PV_Elec_Gas3.csv, the network architecture is designed as follows
...ANSWER
Answered 2021-Jun-09 at 05:18In your forward
method you x.view(-1)
before passing it to a nn.Linear
layer. This "flattens" not only the spatial dimensions on x
, but also the batch dimension! You basically mix together all samples in the batch, making your model dependant on the batch size and in general making the predictions depend on the batch as a whole rather than on the individual data points.
Instead, you should:
QUESTION
I am working on a project for pneumonia detection. I have looked over kaggle for notebooks on the same. there was a user who stacked two pretrained model densenet169 and mobilenet. I copies whole kaggle notebook from the user where he didn't get any error, but when I ran it in google colab I get this error in this part:
part where error is:
...ANSWER
Answered 2021-Jun-07 at 20:58You have mixed up your imports a bit.
Here is a fixed version of your code
QUESTION
I have this dataframe: https://www.kaggle.com/mpwolke/cusersmarildownloadsallcsv
I want to select only those countries whose status has changed over the year. I am clueless as to how can I to achieve this. Can someone please help me.
Thank you.
...ANSWER
Answered 2021-Jun-06 at 15:33Try with groupby filter
.
QUESTION
I want to do a multiple imputation with IterativeImputer.
Here is the dataset (the original is from https://www.kaggle.com/jboysen/mri-and-alzheimers) :
The variables to impute are "educ" and "ses". As they are categorical I've choose to use a classifier (KNeighborsClassifier from sklearn). Predictors are continuous (except "sex").
This is the code :
...ANSWER
Answered 2021-Jun-05 at 18:31I just understood why it does not works. It's because IterativeImputer works only for continuous variables. So, apparently you can't apply multiple imputation for continuous variables with IterativeImputer. There is discussion about this here.
I saw it's possible to do simple imputation with categorical variables in python. However, it does not seem possible to do multiple imputation with this type of variables (anyway, I did not find).
QUESTION
I am learning about text mining and rTweet and I am currently brainstorming on the easiest way to clean text obtained from tweets. I have been using the method recommended on this link to remove URLs, remove anything other than English letters or space, remove stopwords, remove extra whitespace, remove numbers, remove punctuations.
This method uses both gsub and tm_map() and I was wondering if it was possible to stream line the cleaning process using stringr to simply add them to a cleaning pipe line. I saw an answer in the site that recommended the following function but for some reason I am unable to run it.
...ANSWER
Answered 2021-Jun-05 at 02:52To answer your primary question, the clean_tweets()
function is not working in the line "Clean <- tweets %>% clean_tweets
" presumably because you are feeding it a dataframe. However, the function's internals (i.e., the str_
functions) require character vectors (strings).
I say "presumably" here because I'm not sure what your tweets
object looks like, so I can't be sure. However, at least on your test data, the following solves the problem.
QUESTION
I have the dataset having columns....
...ANSWER
Answered 2021-Jun-03 at 15:33Might not be the most efficient solution, but this works.
First, you groupby
the date and concatenate all the tweets for one date:
QUESTION
Hi everyone can you please help me i'm getting this bug with random crop augmentation. TypeError: slice indices must be integers or None or have an index method
Code is below.
...ANSWER
Answered 2021-Jun-03 at 05:20I think the error is in this line:
QUESTION
For my project, I am using tensorflow to predict handwritten user input.
Basically I used this dataset: https://www.kaggle.com/rishianand/devanagari-character-set, and created a model. I used matplotlib to see the images that were being produced by the pixels.
My code essentially works with training data, but i want to up it up a little. Through CV2, I created a GUI that allows users to draw a Nepali Letter. After this, I have branching that tells the program to save the image inside the computer.
This is a snippet of my code for it:
...ANSWER
Answered 2021-Jun-03 at 03:15Understand the dataset:
- the size of the image is 32 x 32
- there are 46 different characters/alphabets
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