Title Portal AtCoder practice contest B Interactive Sorting Problem solution Merge sort + binary for no = 26 n = 26 In the case of n=26, the merge sort requires in the worst case 99 99 99 comparisons. for no = 5 n=5 In the case of n=5, compare c 1 , c 2 c_1,c_2 […]
Tag: entropy
Cross entropy, Focal Loss and its Pytorch implementation
Cross entropy, Focal Loss and its Pytorch implementation Reference link for this article: https://towardsdatascience.com/focal-loss-a-better-alternative-for-cross-entropy-1d073d92d075 Article directory Cross entropy, Focal Loss and its Pytorch implementation 1. Cross entropy 2. Focal loss 3. Pytorch 1. [Cross Entropy](https://pytorch.org/docs/master/generated/torch.nn.CrossEntropyLoss.html?highlight=nn + crossentropyloss#torch.nn.CrossEntropyLoss) 2. [Focal loss](https://github.com/clcarwin/focal_loss_pytorch/blob/master/focalloss.py) 1. Cross entropy The loss is used to update the network parameters through gradient feedback […]
The Beluga optimization algorithm optimizes VMD parameters, the minimum envelope entropy is the fitness function, extracts the IMF component corresponding to the minimum envelope entropy, collects 9 time-domain indicators of the best IMF component, and extracts the feature vector. Take the data of Western Reserve University as an example, with MATLAB code attached
When you read this article, you will definitely have doubts. Isn’t this article the same as the previous article? The previous article is very different, and this article is also an article that I have always wanted to supplement on the basis of the previous article. If you haven’t read my last article, you can […]
Interpretation and application of concepts based on SVM and entropy
— “Computational Thinking and Data Science” Directory 1. SVM 1. Principle of SVM 2. Kernel function of SVM 3. Implementation method of SVM 2. Entropy 1. Basic concepts 2. Principle 3. Examples 4. Application of Entropy in Information Science 1. SVM Support Vector Machine (SVM for short) is a classifier widely used in the field […]
Is the “RL” in RLHF required? Some people use binary cross entropy to fine-tune LLM directly, and the effect is better
Source: Heart of the Machine This article is about 3000 words, it is recommended to read for 5 minutes Human Feedback is available, but this study shows the substitutability of “RL”. Recently, unsupervised language models trained on large datasets have acquired surprising capabilities. However, these models are trained on human-generated data with various goals, priorities, […]
2.3 TensorRT based on Entropy calibration
The pseudocode of tensorRT’s Entropy Calibration, the specific process is as follows: for loop: traverse all possible split points, from 128 to 2048 reference_distribution_P: Cut the original histogram bins according to the current segmentation point i to get the i bins on the left. outliers_count: Cut the original histogram bins according to the current segmentation […]
cross_entropy, binary_cross_entropy, binary_cross_entropy_with_logits
cross_entropy Principle For the specific introduction of the function, refer to the use of torch.nn.functional.cross_entropy The calculation of cross entropy refers to the calculation process of cross entropy loss (Cross Entropy Loss) Example code z = torch.tensor([[1,2],[1,4]],dtype=float) # input tensor y = torch.tensor([0,1]) print(z) print(y) loss1 = torch.nn.functional.cross_entropy(z,y) print(loss1) output tensor([[1., 2.], [1., 4.]], dtype=torch. […]
Correlation method, spectral entropy method, and ratio method for speech endpoint detection (python version)
1. Relevant laws 1. Short-term autocorrelation The autocorrelation function has some properties, such as it is an even function; assuming that the sequence is periodic, its autocorrelation function is also a periodic function of the same period, etc. For voiced speech, the autocorrelation function can be used to find the pitch period of the speech […]
Confusing loss function and activation function in Pytorch [softmax, log_softmax, NLLLoss, CrossEntropy]
Article directory definition activation function softmax T-softmax log_softmax loss function NLL Loss CrossEntropy cross entropy Definition softmax: maps a sequence of values to a probability space (each element is distributed and all sums are 1) log_softmax: Take the logarithm on the basis of softmax NLLLoss: Calculate log_softmax and one-hot CrossEntropy: Measures the difference between two […]
[PyTorch] Section 9: Softmax function and cross entropy function
Author♂?: Let the machine understand languageか Column: PyTorch Description: PyTorch is an open source machine learning library for Python based on Torch. Message: There is no way to go in vain, every step counts! ? Introduction This experiment mainly explains the difference between binary classification problem and multi-classification problem in the classification problem, and the […]