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神经网络算法，股票 开盘 收盘 最高 最低 预测股票的趋势(Neural network algorithm, the stock closed the highest and lowest forecast stock trend)

smote算法实现 smote算法实现 smote算法实现 smote算法实现 smote算法实现 smote算法实现 smote算法实现 

import cv2 import numpy as np import math import matplotlib.pyplot as plt class Hog_descriptor(): def __init__(self, img, cell_size=16, bin_size=8): self.img = img self.img = np.sqrt(img / np.max(img)) self.img = img * 255 self.cell_size = cell_size self.bin_size = bin_size self.angle_unit = 360 / self.bin_size # assert type(self.bin_size) == int, "bin_size should be integer," # assert type(self.cell_size) == int, "cell_size should be integer," # assert type(self.angle_unit) == int, "bin_size should be divisible by 360" def extract(self): height, width = self.img.shape gradient_magnitude, gradient_angle = self.global_gradient() gradient_magnitude = abs(gradient_magnitude) cell_gradient_vector = np.zeros((int(height / self.cell_size), int(width / self.cell_size), self.bin_size)) for i in rang

利用hmmlearn的 GMMHMM,GaussianHMM对金融序列进行隐马尔科夫过程分析！

说明：  详细编写如何让使用cnn识别自己的图片，自己建立cnn模型，可修改(Write in detail how to use CNN to identify their own pictures)

说明：  segmentation image whit kmeans

普通计算器+作图（给函数）+单纯形法计算 (附有文档说明)(calculator+plot for function+Simplex Method （a doc file for introduce）)

实现了多人聊天，采用了tornado，SQLAlchemy框架(To achieve multiplayer chat, the tornado, SQLAlchemy framework is adopted.)

利用geatpy库是实现多目标优化， 基于改进NSGA-Ⅱ算法求解多目标优化问题的进化算法模板，传统NSGA-Ⅱ算法的帕累托最优解来只源于当代种群个体，这样难以高效地获取更多的帕累托最优解，同时难以把种群大小控制在合适的范围内，改进的NSGA2整体上沿用传统的NSGA-Ⅱ算法，不同的是，该算法通过维护一个全局帕累托最优集来实现帕累托前沿的搜索，故并不需要保证种群所有个体都是非支配的。(Using geatpy library to realize multi-objective optimization)

说明：  吴恩达深度学习第一课第二周编程作业，供大家借鉴共享(DeepLearning Lesson 1, Week 2 Programming Assignments)