tensorflow 计算R2/Adjust-R2
时间: 2023-06-12 17:02:45 浏览: 80
在 TensorFlow 中,可以使用以下代码计算 R2 和 Adjusted R2:
```python
import tensorflow as tf
def r_squared(y_true, y_pred):
residual = tf.reduce_sum(tf.square(tf.subtract(y_true, y_pred)))
total = tf.reduce_sum(tf.square(tf.subtract(y_true, tf.reduce_mean(y_true))))
r2_score = tf.subtract(1.0, tf.divide(residual, total))
return r2_score
def adj_r_squared(y_true, y_pred, n, k):
r2 = r_squared(y_true, y_pred)
adj_r2 = 1 - ((1 - r2) * tf.cast(n - 1, "float32")) / tf.cast(n - k - 1, "float32")
return adj_r2
```
其中,y_true 是真实值,y_pred 是预测值,n 是样本数,k 是特征数。使用这两个函数可以分别计算 R2 和 Adjusted R2。
相关问题
image_stitching.py: error: the following arguments are required: -i/--images, -o/--output
As an AI language model, I don't have access to the specific code or files you are referring to. However, the error message suggests that you need to provide the input and output arguments when running the image_stitching.py script.
The -i or --images argument indicates the path to the input images that you want to stitch together. The -o or --output argument specifies the output file name or path where you want to save the resulting stitched image.
For example, if you have a folder named "images" containing a set of images you want to stitch together and you want to save the output as "result.jpg", you can run the script with the following command:
python image_stitching.py --images images/ --output result.jpg
Make sure to replace "image_stitching.py" with the actual name and path of the script file, and adjust the input and output paths according to your needs.
WARNING:tensorflow:From /home/chb/anaconda3/envs/deepmd2/lib/python3.10/site-packages/tensorflow/python/compat/v2_compat.py:107: disable_resource_variables (from tensorflow.python.ops.variable_scope) is deprecated and will be removed in a future version. Instructions for updating: non-resource variables are not supported in the long term WARNING:root:To get the best performance, it is recommended to adjust the number of threads by setting the environment variables OMP_NUM_THREADS, TF_INTRA_OP_PARALLELISM_THREADS, and TF_INTER_OP_PARALLELISM_THREADS. See https://deepmd.rtfd.io/parallelism/ for more information.
这不是一个问题,而是一个警告信息。在使用 TensorFlow 运行 DeepMD 模型时,建议设置环境变量 OMP_NUM_THREADS、TF_INTRA_OP_PARALLELISM_THREADS 和 TF_INTER_OP_PARALLELISM_THREADS,以获得更好的性能。您可以访问 https://deepmd.rtfd.io/parallelism/ 获取更多信息。
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