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I have been using version v1.1.1 for some time now and have been able to successfully load large amounts of data (5-10 GB) into memory using XGBoost and DMatrix, as I have ample RAM to do so. However,…
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# What code produced the error?
```R
library(forecast)
library(M4metalearning)
load("model_M4.rda")
tr
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Currently trying to use the standalone version to identify phages in coxiella.
First I created an input file to PhageBoost with:
```
esearch -db genome -query "txid776 [Organism]"|elink -tar…
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## Describe your environment
* Operating system: Ubuntu 22.04.3 LTS
* Python Version: Python 3.10.12
* CCXT version: ccxt==4.2.78
* Freqtrade Version: freqtrade 2024.3-dev-7d6d3d38f…
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Using a multi-class model created with ``.
```
from pycaret.classification import *
import shap
shap.initjs()
experiment = setup(df, 'AGE_GRP', silent=True, session_id=42)
model = create_…
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Hi Pablojrios,
I am interested in this project. There are lots of stuff here and mixed up. I cannot figure it out where to start. So, could you please give an instruction on how to use these code s…
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```
from sklearn.linear_model import Ridge, Lasso, ElasticNet
from sklearn.ensemble import RandomForestRegressor
from xgboost import XGBRegressor
from lightgbm import LGBMRegressor
from vaex.ml.s…
jahoy updated
2 years ago
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Hello Jay,
A great video as usual. Explainable AI is a critical component to bring the AI revolution to many business areas.
I thought you might be interested in this opensource package: https://g…
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Hi, after reading your Medium article, I tried to reproduce results using your jupyter notebook and found one minor issue and one major issue when running `xg_random.fit(X_train, y_train)` in code bl…
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1. Use the existing map to label the existing turning points on the map
2. Training model based on the tracks and the labelled turning points
3. Test the trained model on raw tracks.