搜索资源列表
ML_Automata
- Learning Automata Algorithms A collection of machine learning programs which contains some of Learning Automata algorithms such as Tsetline, Krinisky, Krylov, LRI, LIP, LRR, LReP, SoftMax, SampleAverage and Random strategy. All of these develope
RecognizeIt-v4.0-(softmax)
- 基于神经网络的手势识别程序 手写输入原理的演示-Gesture Recognition Based on Neural Network program demonstrates the principle of handwriting input
twodimapproximationbp
- 单输出函数Y=SIN(X)逼近问题的bp程序:假设网络结构为3--2--1，输入维数M,共N个样本,一般输入不算层，输出算层- 激活函数: hardlim---(0,1),hardlims---（-1,1),purelin,logsig---(0,1),tansig----(-1,1) softmax,poslin,radbas,satlin,satlins,tribas 训练算法: 1.traingd,traingdm,traingda(variable l
Exercise5-Softmax-Regression
- 斯坦福深度学习教程中关于softmax regression的练习代码，源代码中需要补全的地方，全部把代码补完整，把手写体识别的数据库放到路径下，可以直接运行-Stanford deep learning tutorial exercises on softmax regression code, source code need to fill all places, all the full complement of the code, the handwriting recognitio
UFLDL
- UFLDL作业，以下作业均已完整做好，build deep network,vectorization,softmax,working with large images,pca。-UFLDL,build deep network,vectorization,softmax,working with large images,pca
softmax_exercise
- 该文档办了深度学习中Softmax问题的详细程序和代码-this document contain softmax of deeplearning network
softmax-regression
- softmax 回归源代码（高维logistic回归 ）进行邮件文本分类。-softmax regression to classify for email text.(high dimension of logistic regression)
libORF-master
- 针对各种机器学习，深度学习领域的一个matlab工具包-A machine learning library focused on deep learning.Following algorithms and models are provided along with some static utility classes: - Naive Bayes, Linear Regression, Logistic Regression, Softmax Regression, Linear S
stackedAE
- 堆栈自编码，通过两个稀疏自编码的堆叠和softmax分类模型，实现手写体的分类。-Stack self-encoding, since encoding by two sparse stack and softmax classification model to classify handwriting.
self-taught-learning
- 自主学习把稀疏自编码器和分类器实现结合。先通过稀疏自编码对无标签的5-9的手写体进行训练得到最优参数，然后通过前向传播，得到训练集和测试集的特征，通过0-4有标签训练集训练出softmax模型，然后输入测试集到分类模型实现分类。-Independent Learning the encoder and the sparse classifiers achieve the combination. First through sparse coding since no label was ha
Softmax_exercise
- Softmax用于多分类问题，本例是将MNIST手写数字数据库中的数据0-9十个数字进行分类，其中训练样本有6万个，测试样本有1万个数字是0~9-Softmax for multi classification problems, the present case is the handwritten data MNIST digital 0-9, classification, training samples which have 60,000, there are 10,000 test
stacked-autoencoder
- 基于两层的层叠自编码的深度学习模型，前两层用于特征提取，再加一个Softmax分类器用于分类-Two stacked the depth of learning coding model based on the first two levels for feature extraction, coupled with a classifier for classifying Softmax
softmax
- MATLAB实现softmax,测试类主要采用mnist-implement a simple softmax in matlab
Softmax
- 一个小demo,用softmax实现数据分类，数据有4类，均服从高斯分布-A small demo, a classifier with softmax softmax is implemented to classify 4 classes of datas which are generated by gaussian distribution
Classifier-based-Softmax
- 一个小demo,用softmax实现数据分类，数据有4类，均服从高斯分布-A little demo, a classifier with softmax softmax is implemented to classify 4 classes of datas which are generated by gaussian distribution
FullBNT-1.0.4
- 创建你的第一个贝叶斯网络 手工创建一个模型 从一个文件加载一个模型 使用 GUI 创建一个模型 推断 处理边缘分布 处理联合分布 虚拟证据 最或然率解释 条件概率分布 列表（多项式）节点 Noisy-or 节点 其它（噪音）确定性节点 Softmax（多项式 分对数）节点 神经网络节点 根节点 高斯节点 广义线性模型节点 分类 / 回归树节点 其它连续分布 CPD 类型摘要 模型举例 高斯混合模型 PCA、ICA等 专家系统的混合 专家系统的分等级混合 QMR 条件高斯模型 其它混合模型 参数学
CNN
- 一个卷积层+一个下采样+softmax实现mnist识别(implement a simple CNN)
comp4021-assignment2-svg-master
- Comp course program for image classification. The classifier may be SoftMax or SVM to calculate the loss.
softmax
- 人工智能导论作业，用softmax方法实现的水杯图片分类，可扩展到其他分类任务(Homework of AI. Classify images of cups using softmax. Can be used in other tasks.)
Softmax_Identification
- SOFTMAX classifier, added to the MATLAB path, and then directly call the line