Tremendous Metrics
Project description
Tremetrics
Tremendous Metrics.
Installation
You can install Tremetrics from PyPi using pip.
pip install tremetrics
Usage
ConfusionMatrix
from tremetrics import ConfusionMatrix
y_true, y_pred = ... # Generate predictions
cm = ConfusionMatrix.from_pred(y_true, y_pred) # Create a new confusion matrix object
print(cm) # Print the confusion matrix
array_for_further_use = cm.array # Get the matrix as a numpy array
print(cm.tp, cm.fn, cm.fp, cm.tn) # Get the individual quadrant values
print(cm.get_latex_table(multirow=True)) # Get the matrix as code for a Latex table
print(cm.recall_score(average='micro')) # Call any sklearn.metrics function using the data in the matrix
Project details
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
tremetrics-0.1.3.tar.gz
(3.6 kB
view details)
Built Distribution
Filter files by name, interpreter, ABI, and platform.
If you're not sure about the file name format, learn more about wheel file names.
Copy a direct link to the current filters
File details
Details for the file tremetrics-0.1.3.tar.gz.
File metadata
- Download URL: tremetrics-0.1.3.tar.gz
- Upload date:
- Size: 3.6 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/3.7.1 importlib_metadata/4.8.1 pkginfo/1.8.2 requests/2.27.1 requests-toolbelt/0.9.1 tqdm/4.62.3 CPython/3.7.4
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
a3815ca2d0e81b1760ca6fb6891b181cb45d6a83386d1221818ad456b63b28bc
|
|
| MD5 |
5b2f025328d1aecc8d7db05f2ae14b45
|
|
| BLAKE2b-256 |
168c10fc714518df586900ea57db81ea8becbfca894fbdb51107f2ffa6d35057
|
File details
Details for the file tremetrics-0.1.3-py3-none-any.whl.
File metadata
- Download URL: tremetrics-0.1.3-py3-none-any.whl
- Upload date:
- Size: 4.3 kB
- Tags: Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/3.7.1 importlib_metadata/4.8.1 pkginfo/1.8.2 requests/2.27.1 requests-toolbelt/0.9.1 tqdm/4.62.3 CPython/3.7.4
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
062893c307c6bed2ceeacf6d199b52f056cff5ee7f165a8c0c4c8b44ea10de57
|
|
| MD5 |
fca65308a27a84d69f1c76e66e778f47
|
|
| BLAKE2b-256 |
c2bbc72372ce8e5d3f4d3710055b819e9863cd7a20340df1895217b0e1287476
|