add dataset_info in dataset metadata
Browse files
README.md
CHANGED
@@ -17,6 +17,809 @@ task_categories:
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task_ids:
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18 |
- univariate-time-series-forecasting
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- multivariate-time-series-forecasting
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---
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21 |
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# Dataset Card for Monash Time Series Forecasting Repository
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@@ -229,4 +1032,4 @@ The annotations come from the datasets listed in the table above.
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### Contributions
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-
Thanks to [@kashif](https://github.com/kashif) for adding this dataset.
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17 |
task_ids:
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- univariate-time-series-forecasting
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19 |
- multivariate-time-series-forecasting
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dataset_info:
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- config_name: weather
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features:
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- name: start
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dtype: timestamp[s]
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- name: target
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sequence: float32
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- name: feat_static_cat
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+
sequence: uint64
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- name: feat_dynamic_real
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sequence:
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sequence: float32
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- name: item_id
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dtype: string
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splits:
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- name: test
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num_bytes: 177638713
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num_examples: 3010
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- name: train
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39 |
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num_bytes: 176893738
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40 |
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num_examples: 3010
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- name: validation
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42 |
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num_bytes: 177266226
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43 |
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num_examples: 3010
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+
download_size: 38820451
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dataset_size: 531798677
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- config_name: tourism_yearly
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features:
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48 |
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- name: start
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dtype: timestamp[s]
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- name: target
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51 |
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sequence: float32
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52 |
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- name: feat_static_cat
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53 |
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sequence: uint64
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54 |
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- name: feat_dynamic_real
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55 |
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sequence:
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sequence: float32
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- name: item_id
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58 |
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dtype: string
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59 |
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splits:
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60 |
+
- name: test
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61 |
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num_bytes: 71358
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62 |
+
num_examples: 518
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63 |
+
- name: train
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64 |
+
num_bytes: 54264
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65 |
+
num_examples: 518
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66 |
+
- name: validation
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67 |
+
num_bytes: 62811
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68 |
+
num_examples: 518
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69 |
+
download_size: 36749
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70 |
+
dataset_size: 188433
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- config_name: tourism_quarterly
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features:
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73 |
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- name: start
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74 |
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dtype: timestamp[s]
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- name: target
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76 |
+
sequence: float32
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77 |
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- name: feat_static_cat
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78 |
+
sequence: uint64
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79 |
+
- name: feat_dynamic_real
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80 |
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sequence:
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81 |
+
sequence: float32
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82 |
+
- name: item_id
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83 |
+
dtype: string
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84 |
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splits:
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85 |
+
- name: test
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86 |
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num_bytes: 190920
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87 |
+
num_examples: 427
|
88 |
+
- name: train
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89 |
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num_bytes: 162738
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90 |
+
num_examples: 427
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91 |
+
- name: validation
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92 |
+
num_bytes: 176829
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93 |
+
num_examples: 427
|
94 |
+
download_size: 93833
|
95 |
+
dataset_size: 530487
|
96 |
+
- config_name: tourism_monthly
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97 |
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features:
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98 |
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- name: start
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99 |
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dtype: timestamp[s]
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100 |
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- name: target
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101 |
+
sequence: float32
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102 |
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- name: feat_static_cat
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103 |
+
sequence: uint64
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104 |
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- name: feat_dynamic_real
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105 |
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sequence:
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106 |
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sequence: float32
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107 |
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- name: item_id
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108 |
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dtype: string
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109 |
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splits:
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110 |
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- name: test
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111 |
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num_bytes: 463986
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112 |
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num_examples: 366
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113 |
+
- name: train
|
114 |
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num_bytes: 391518
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115 |
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num_examples: 366
|
116 |
+
- name: validation
|
117 |
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num_bytes: 427752
|
118 |
+
num_examples: 366
|
119 |
+
download_size: 199791
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120 |
+
dataset_size: 1283256
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121 |
+
- config_name: cif_2016
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122 |
+
features:
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123 |
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- name: start
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124 |
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dtype: timestamp[s]
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125 |
+
- name: target
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126 |
+
sequence: float32
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127 |
+
- name: feat_static_cat
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128 |
+
sequence: uint64
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129 |
+
- name: feat_dynamic_real
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130 |
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sequence:
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131 |
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sequence: float32
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132 |
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- name: item_id
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133 |
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dtype: string
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134 |
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splits:
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135 |
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- name: test
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136 |
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num_examples: 72
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138 |
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- name: train
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139 |
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140 |
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num_examples: 72
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141 |
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- name: validation
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142 |
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num_bytes: 28295
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143 |
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num_examples: 72
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144 |
+
download_size: 53344
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145 |
+
dataset_size: 84885
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146 |
+
- config_name: london_smart_meters
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147 |
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features:
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148 |
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- name: start
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149 |
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dtype: timestamp[s]
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150 |
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- name: target
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151 |
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sequence: float32
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152 |
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- name: feat_static_cat
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153 |
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sequence: uint64
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154 |
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- name: feat_dynamic_real
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155 |
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sequence:
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156 |
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sequence: float32
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157 |
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158 |
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dtype: string
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159 |
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splits:
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160 |
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161 |
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162 |
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163 |
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- name: train
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164 |
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165 |
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166 |
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- name: validation
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167 |
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num_bytes: 685762294
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168 |
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num_examples: 5560
|
169 |
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download_size: 219673439
|
170 |
+
dataset_size: 2057286882
|
171 |
+
- config_name: australian_electricity_demand
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172 |
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features:
|
173 |
+
- name: start
|
174 |
+
dtype: timestamp[s]
|
175 |
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- name: target
|
176 |
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sequence: float32
|
177 |
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- name: feat_static_cat
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178 |
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sequence: uint64
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179 |
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- name: feat_dynamic_real
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180 |
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181 |
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sequence: float32
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182 |
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- name: item_id
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183 |
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dtype: string
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184 |
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185 |
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186 |
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188 |
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191 |
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192 |
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193 |
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num_examples: 5
|
194 |
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download_size: 5770526
|
195 |
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dataset_size: 14293199
|
196 |
+
- config_name: wind_farms_minutely
|
197 |
+
features:
|
198 |
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---
|
824 |
|
825 |
# Dataset Card for Monash Time Series Forecasting Repository
|
|
|
1032 |
|
1033 |
### Contributions
|
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|
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+
Thanks to [@kashif](https://github.com/kashif) for adding this dataset.
|