官术网_书友最值得收藏!

Getting ready

To predict a stock price, we will perform the following steps:

  1. Order the dataset from the oldest to the newest date.
  2. Take the first five stock prices as input and the sixth stock price as output.
  3. Slide it across so that in the next data point the second to the sixth data points are input and the seventh data point is the output, and so on, till we reach the final data point.
  4. Given that it is a continuous number that we are predicting, the loss function this time shall be the mean squared error value.

Additionally, we will also try out the scenario where we integrate the text data into the historic numeric data to predict the next day's stock price.

主站蜘蛛池模板: 泗水县| 铜陵市| 筠连县| 乐都县| 夹江县| 申扎县| 罗甸县| 扶绥县| 嵊州市| 五台县| 云龙县| 从化市| 中阳县| 水富县| 县级市| 渑池县| 淮滨县| 江西省| 莫力| 乐山市| 桃园县| 汶上县| 攀枝花市| 黄梅县| 山阳县| 车险| 乡宁县| 建平县| 济南市| 台江县| 天等县| 凤凰县| 安塞县| 体育| 南投县| 冀州市| 徐汇区| 普陀区| 博兴县| 科尔| 惠东县|