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DataCanvasIO
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HyperTS
A Full-Pipeline Automated Time Series (AutoTS) Analysis Toolkit.
https://hyperts.readthedocs.io
Apache License 2.0
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指定mode为dl会报错
#114
Bang0518
closed
3 months ago
10
AttributeError: module 'pandas' has no attribute 'Int64Index'
#113
Billy1900
closed
5 months ago
3
請問範例中用mode:'stats' 且task = multivariate-forecast時, predict 是如何預測的?
#112
02hao09
closed
6 months ago
2
关于make_experiment参数的问题
#111
shuangshui
closed
7 months ago
5
Some Issues on Time Series Prediction Results
#110
Layonhuuu
closed
8 months ago
25
按照指示，无法配置好环境
#109
13012473536
closed
9 months ago
1
Stopped training because there are no more leaves that meet the split requirements
#108
hello-the-vsworld
closed
10 months ago
3
预测时不预测负值，只预测正值
#107
hello-the-vsworld
closed
10 months ago
5
最终预测结果图片样式
#106
hello-the-vsworld
closed
11 months ago
3
Why 100% accuracy classification already in First epoch?
#105
ericleonardo
closed
11 months ago
1
怎样查看所选择的算法，以及算法的具体模型参数？
#104
hello-the-vsworld
opened
11 months ago
1
max_trials 设置最大搜索次数
#103
hello-the-vsworld
closed
1 year ago
4
[fix] seems like a typo
#101
NatLee
closed
1 year ago
0
Could you give an example for converting Hyperts trainning model to PMML file?
#100
mengzhizihu
closed
1 year ago
1
Need at least 3 dates to infer frequency
#99
hello-the-vsworld
closed
1 year ago
11
ImportError: DLL load failed while importing _xxhash: 内存资源不足，无法处理此命令。
#98
Strom-x
closed
1 year ago
0
how to use two datasets in hyperts
#97
kelvin-ksl
closed
1 year ago
2
When I git clone the repo and pip install -e . , the setup can't work correct.
#96
RuixiangS
closed
1 year ago
4
Need at least 3 dates to infer frequency
#95
kelvin-ksl
closed
1 year ago
0
TypeError: ufunc 'isnan' not supported for the input types, and the inputs could not be safely coerced to any supported types according to the casting rule ''safe''
#94
kelvin-ksl
closed
1 year ago
9
AttributeError: 'NoneType' object has no attribute 'get_pipeline_params'
#93
kelvin-ksl
closed
1 year ago
3
dl模式下模型保存报错
#92
wangjianqiao111
closed
1 year ago
3
回归预测结果解释
#91
wangjianqiao111
closed
1 year ago
7
回归预测失败
#90
wangjianqiao111
closed
1 year ago
2
回归任务数据格式确定
#89
wangjianqiao111
closed
1 year ago
0
stat模式和dl模式都不支持时间序列回归和分类吗？如果是，那什么模式可以做回归和分类？
#88
wangjianqiao111
closed
1 year ago
1
分类任务和回归任务时参数怎么设置
#87
wangjianqiao111
closed
1 year ago
9
Rename Hybird to hybrid
#86
braj29
closed
1 year ago
1
ModuleNotFoundError: No module named 'backports.zoneinfo'
#85
943fansi
closed
1 year ago
3
参数解释
#84
wangjianqiao111
closed
1 year ago
2
版本介绍
#83
wangjianqiao111
closed
1 year ago
2
more information about build_input_head
#82
943fansi
closed
1 year ago
5
加载第三方模型报错
#81
xiehuanyi
closed
1 year ago
1
时序预测模型训练问题
#80
jelly909
closed
1 year ago
3
单变量时序预测报错问题
#78
wuzhitao
closed
1 year ago
10
Support numpy >= 1.22
#77
DManowitz
closed
1 year ago
1
hyperts for time series regression example
#76
bhralzz
opened
1 year ago
1
自动训练的融合dl模型，做predict预测时报错 |ValueError: cannot reshape array of size 63 into shape (1,newaxis,2)
#73
yanglonghu
closed
1 year ago
5
ImportError: DLL load failed while importing _parquet: 内存资源不足，无法处理此命令
#72
mokeeqian
closed
1 year ago
3
ValueError: decay is deprecated in the new Keras optimizer, pleasecheck the docstring for valid arguments, or use the legacy optimizer, e.g., tf.keras.optimizers.legacy.Adam.
#71
zhangxjohn
closed
1 year ago
0
Support scipy >=1.8.0
#70
DManowitz
opened
1 year ago
4
Support for prophet >= 1.1
#69
DManowitz
opened
1 year ago
1
AttributeError: module 'featuretools.primitives' has no attribute 'Library'
#68
HamletMonkey
closed
1 year ago
2
关于 HybirdRNN 解决多变量时序分类的问题
#67
Shanshan122
closed
1 year ago
5
None: marshal data too short
#66
benpaobamingliang1
opened
1 year ago
5
data_cleaner_args 参数问题
#65
Shanshan122
closed
1 year ago
2
Support ConvVAE model for anomaly detection task.
#64
zhangxjohn
opened
1 year ago
0
Support OneClassSVM model for anomaly detection task.
#63
zhangxjohn
opened
1 year ago
0
Support IsolationForest model for anomaly detection task.
#62
zhangxjohn
opened
1 year ago
0
我有29个特征变量进行时序分类，DL模式和NAS模式模型出错
#61
czstudio
closed
1 year ago
2
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