3. Homework 1: COVID-19 Cases Prediction (Regression) 实验目的: 熟悉PyTorch。 了解基本的DNN培训技巧。 使用深度神经网络(DNN)解决回归问题。 下载数据集: !gdown --id '1kLSW_-cW2Huj7bh84YTdimGBOJaODiOS' --output covid.train.csv !gdown --id '1iiI5qROrAhZn-o4FPqsE97bMzDEFvIdg' --output...
1.目标 Solve a regression problem withdeep neural networks(DNN). Understand basic DNN training tips. Familiarize yourself with PyTorch. 2.任务描述 Given survey results in the past 5 days in a specific state in U.S., then predict the percentage of new tested positive cases in the 5 th day...
1、深度学习调参 努力的方向比付出的努力更加重要,就作业01Regression而言,特征选择比调超参数更有效得多。 2、就作业01Regression而言,采用Adam优化器的初始学习率可以取得大一些,SGD的初始学习率太大的化,就会使得训练无法进行,即train loss和valid loss很大,这个现象不确定是否为普遍现象? 3、目前kaggle榜单上排名最...
class COVID19Dataset(Dataset): ''' Dataset for loading and preprocessing the COVID19 dataset ''' def __init__(self, data, mode='train'): self.mode = mode self.data = data def __getitem__(self, index): if self.mode in ['train', 'val']: return self.data.iloc[index, :-1]....
简介:COVID-19 Cases Prediction (Regression) Feature Selection Choose features you deem useful by modifying the function below. def select_feat(train_data, valid_data, test_data, select_all=True):'''Selects useful features to perform regression'''y_train, y_valid = train_data[:,-1], vali...
COVID-19 Cases Prediction Source: Delphi group @ CMU A daily survey since April 2020 via facebook. Try to find out the data and use it to your training is forbidden Given survey results in the past 5 days in a specific state in U.S., then predict the percentage of new tested positiv...
there is an urgent need to predict confirmed cases so as to analyze the impact of COVID-19 and practice readiness in healthcare systems.This study uses gradient boosting regression(GBR)to build a trained model to predict the daily total confirmed cases of COVID-19.The GBR method can ...
李宏毅2021机器学习HW1 在Google Colab中运行成功,未在PP中运行 - 飞桨AI Studio
Our framework can foresee peak corona cases with an R-Squared value of 0.986 utilizing linear regression and fall of this pandemic at various levels for countries like India, US, and Brazil. We found that considering more countries for training degrades the prediction process as constraints vary ...
simple baseline过很简单,每行数据不做任何处理,直接作为网络的输入就行,网络也不用优化。 medium baseline需要加一些优化。 首先前面表示州的one-hot向量过于稀疏,所以我直接忽略。 由于输入数据全是正数,而且我使用了relu,所以训练中有时会导致loss一直不变,所以我将输入数据进行了归一化。