一旦你完成了上面步骤的代码,你就能用submission.to_csv('kaggle.csv, index=False')输出一个csv结果。 这将会给你的第一个条件所有需要的东西——虽然这没有给你很好的准确率。(~0.75) 由于我们的预测在不同的数据集上导致在测试集上的分数低于我们在交叉验证上的分数。 在下一个任务中我们将学习如何生成更好...
model.predict(test)# select the indix with the maximum probabilityresults = np.argmax(results,axis =1) results = pd.Series(results,name="Label") submission = pd.concat([pd.Series(range(1,28001),name ="ImageId"),results],axis =1) submission.to_csv("cnn_mnist_datagen.csv",index=False...
to_csv('submission.csv', index=False) 6 Pipline from sklearn.compose import ColumnTransformer from sklearn.pipeline import Pipeline from sklearn.impute import SimpleImputer from sklearn.preprocessing import OneHotEncoder # Preprocessing for numerical data numerical_transformer = SimpleImputer(strategy...
'TotRmsAbvGrd'和'GrLiveArea'面积越大,而且房间数量越多,房价也会越高。 ‘YearBuilt’建造年份,房价一般随时间越来越贵 最终我们需要考虑的特征如下: 3.3 绘制关系图 In [21]: sns.set() cols = ['SalePrice','OverallQual','GrLivArea', 'GarageCars','TotalBsmtSF', 'FullBath', 'TotRmsAbvGrd',...
import Polarfrom pyecharts import Overlapfrom pylab import mplmpl.rcParams['font.sans-serif'] = ['SimHei'] # 指定默认字体mpl.rcParams['axes.unicode_minus'] =False#数据读入data = pd.read_csv('./athlete_events.csv',engine='python')data_mapping = pd.read_csv('./noc_regions.csv',engine...
to_csv(fname, index=False) if hasattr(self.learner.learner, "predict_proba"): if self.plot_importance: feature_names = self.feature._get_feature_names() y_proba = self.learner.learner.predict_proba(X_test, feature_names) else: y_proba = self.learner.learner.predict_proba(X_test) f...
['has2ndfloor']=df['2ndFlrSF'].apply(lambdax:1ifx>0else0)df['hasgarage']=df['GarageArea'].apply(lambdax:1ifx>0else0)df['hasbsmt']=df['TotalBsmtSF'].apply(lambdax:1ifx>0else0)df['hasfireplace']=df['Fireplaces'].apply(lambdax:1ifx>0else0)df.to_csv(PATH/'features.csv',...
Choose YOLOv8 PyTorch TXT when asked in what format you want to export your data. You will see a dropdown with various options like this: Congratulations, you have successfully converted your dataset from Kaggle Wheat CSV format to YOLOv8 PyTorch TXT format!
submission.to_csv('../result/submission1.csv', index=False) 注意代码中的这两行: train = pd.read_csv('../data/train.csv') test = pd.read_csv('../data/test.csv') submission.to_csv('../result/submission1.csv', index=False) ...
return nomalizing(toInt(data)) 分析knn_benchmark.csv 前面已经提到,由于digit recognition是训练赛,所以这个文件是官方给出的参考结果,本来可以不理这个文件的,但是我下面为了对比自己的训练结果,所以也把knn_benchmark.csv这个文件读取出来,这个文件里的数据是28001*2,第一行是文字说明,可以去掉,第一列表示图片...