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| author | Xiangrui Meng <meng@databricks.com> | 2014-05-19 21:29:33 -0700 |
|---|---|---|
| committer | Tathagata Das <tathagata.das1565@gmail.com> | 2014-05-19 21:29:33 -0700 |
| commit | bcb9dce6f444a977c714117811bce0c54b417650 (patch) | |
| tree | d12d9ba87dcf5d85edc38f082adbb6fae2a19052 /data | |
| parent | b0ce22e071da4cc62ec5e29abf7b1299b8e4a6b0 (diff) | |
| download | spark-bcb9dce6f444a977c714117811bce0c54b417650.tar.gz spark-bcb9dce6f444a977c714117811bce0c54b417650.tar.bz2 spark-bcb9dce6f444a977c714117811bce0c54b417650.zip | |
[SPARK-1874][MLLIB] Clean up MLlib sample data
1. Added synthetic datasets for `MovieLensALS`, `LinearRegression`, `BinaryClassification`.
2. Embedded instructions in the help message of those example apps.
Per discussion with Matei on the JIRA page, new example data is under `data/mllib`.
Author: Xiangrui Meng <meng@databricks.com>
Closes #833 from mengxr/mllib-sample-data and squashes the following commits:
59f0a18 [Xiangrui Meng] add sample binary classification data
3c2f92f [Xiangrui Meng] add linear regression data
050f1ca [Xiangrui Meng] add a sample dataset for MovieLensALS example
Diffstat (limited to 'data')
| -rw-r--r-- | data/mllib/sample_binary_classification_data.txt | 100 | ||||
| -rwxr-xr-x | data/mllib/sample_linear_regression_data.txt | 501 | ||||
| -rw-r--r-- | data/mllib/sample_movielens_data.txt | 1501 |
3 files changed, 2102 insertions, 0 deletions
diff --git a/data/mllib/sample_binary_classification_data.txt b/data/mllib/sample_binary_classification_data.txt new file mode 100644 index 0000000000..861c70cde7 --- /dev/null +++ b/data/mllib/sample_binary_classification_data.txt @@ -0,0 +1,100 @@ +0 128:51 129:159 130:253 131:159 132:50 155:48 156:238 157:252 158:252 159:252 160:237 182:54 183:227 184:253 185:252 186:239 187:233 188:252 189:57 190:6 208:10 209:60 210:224 211:252 212:253 213:252 214:202 215:84 216:252 217:253 218:122 236:163 237:252 238:252 239:252 240:253 241:252 242:252 243:96 244:189 245:253 246:167 263:51 264:238 265:253 266:253 267:190 268:114 269:253 270:228 271:47 272:79 273:255 274:168 290:48 291:238 292:252 293:252 294:179 295:12 296:75 297:121 298:21 301:253 302:243 303:50 317:38 318:165 319:253 320:233 321:208 322:84 329:253 330:252 331:165 344:7 345:178 346:252 347:240 348:71 349:19 350:28 357:253 358:252 359:195 372:57 373:252 374:252 375:63 385:253 386:252 387:195 400:198 401:253 402:190 413:255 414:253 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