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Strong and weak sampling

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are two sampling approach in Statistics, and are popular in computational cognitive science and language learning. In strong sampling, it is assumed that the data are intentionally generated as positive examples of a concept, while in weak sampling, it is assumed that the data are generated without
300: 193: 289: 544:{\displaystyle P(h|x)={\frac {P(x|h)P(h)}{\sum \limits _{h'}P(x|h')P(h')}}={\begin{cases}{\frac {P(h)}{\sum \limits _{h':x\in h'}P(h')}}&{\text{, if }}x\in h\\0&{\text{, otherwise}}\end{cases}}} 91: 661:"Sampling assumptions in language learning 1 Running head: SAMPLING ASSUMPTIONS IN LANGUAGE LEARNING Sampling assumptions affect use of indirect negative evidence in language learning" 206: 593: 660: 618: 800: 819: 793: 188:{\displaystyle P(x|h)={\begin{cases}{\frac {1}{|h|}}&{\text{, if }}x\in h\\0&{\text{, otherwise}}\end{cases}}} 824: 786: 284:{\displaystyle P(x|h)={\begin{cases}1&{\text{, if }}x\in h\\0&{\text{, otherwise}}\end{cases}}} 758: 432: 238: 123: 638: 51: 723: 556: 713: 32: 598: 770: 744: 679: 813: 718: 766: 701: 41: 727: 21: 639:"Bayesian word learning Sensitivity to sampling in Bayesian word learning" 86:, we assume observation is randomly sampled from the true hypothesis: 201:, we assume observations randomly sampled and then classified: 15: 537: 277: 181: 774: 46: 36: 294:
Consequence: Posterior computation under Weak Sampling
601: 559: 303: 209: 94: 702:"Sampling assumptions in inductive generalization" 612: 587: 543: 283: 187: 794: 8: 801: 787: 717: 600: 569: 558: 529: 506: 456: 435: 427: 388: 368: 339: 327: 313: 302: 269: 246: 233: 219: 208: 173: 150: 140: 132: 126: 118: 104: 93: 629: 680:"Lecture 20: Strong vs weak sampling" 7: 755: 753: 745:Lecture 20: Strong vs weak sampling 453: 365: 14: 757: 719:10.1111/j.1551-6709.2011.01212.x 20: 687:Computational Cognitive Science 582: 570: 563: 498: 487: 447: 441: 418: 407: 401: 389: 382: 359: 353: 347: 340: 333: 321: 314: 307: 227: 220: 213: 141: 133: 112: 105: 98: 1: 773:. You can help Knowledge by 841: 752: 553:Therefore the likelihood 700:Navarro, Daniel (2012). 648:. Developmental Science. 71:Strong and weak sampling 588:{\displaystyle P(x|h')} 35:, as no other articles 769:-related article is a 614: 589: 545: 285: 189: 820:Sampling (statistics) 615: 590: 546: 286: 190: 599: 557: 301: 207: 92: 678:Navarro, Danielle. 620:will be "ignored". 595:for all hypotheses 613:{\displaystyle h'} 610: 585: 541: 536: 483: 378: 281: 276: 185: 180: 74:any restrictions. 54:for suggestions. 44:to this page from 782: 781: 706:Cognitive Science 532: 509: 502: 452: 422: 364: 272: 249: 176: 153: 146: 78:Formal Definition 68: 67: 832: 825:Statistics stubs 803: 796: 789: 761: 754: 732: 731: 721: 697: 691: 690: 684: 675: 669: 668: 656: 650: 649: 643: 634: 619: 617: 616: 611: 609: 594: 592: 591: 586: 581: 573: 550: 548: 547: 542: 540: 539: 533: 530: 510: 507: 503: 501: 497: 482: 481: 464: 450: 436: 423: 421: 417: 400: 392: 377: 376: 362: 343: 328: 317: 290: 288: 287: 282: 280: 279: 273: 270: 250: 247: 223: 194: 192: 191: 186: 184: 183: 177: 174: 154: 151: 147: 145: 144: 136: 127: 108: 63: 60: 49: 47:related articles 24: 16: 840: 839: 835: 834: 833: 831: 830: 829: 810: 809: 808: 807: 750: 741: 736: 735: 699: 698: 694: 682: 677: 676: 672: 658: 657: 653: 641: 636: 635: 631: 626: 602: 597: 596: 574: 555: 554: 535: 534: 527: 521: 520: 504: 490: 474: 457: 451: 437: 428: 410: 393: 369: 363: 329: 299: 298: 296: 275: 274: 267: 261: 260: 244: 234: 205: 204: 179: 178: 171: 165: 164: 148: 131: 119: 90: 89: 84:strong sampling 80: 64: 58: 55: 45: 42:introduce links 25: 12: 11: 5: 838: 836: 828: 827: 822: 812: 811: 806: 805: 798: 791: 783: 780: 779: 762: 748: 747: 740: 739:External links 737: 734: 733: 712:(2): 187–223. 692: 670: 651: 628: 627: 625: 622: 608: 605: 584: 580: 577: 572: 568: 565: 562: 538: 528: 526: 523: 522: 519: 516: 513: 505: 500: 496: 493: 489: 486: 480: 477: 473: 470: 467: 463: 460: 455: 449: 446: 443: 440: 434: 433: 431: 426: 420: 416: 413: 409: 406: 403: 399: 396: 391: 387: 384: 381: 375: 372: 367: 361: 358: 355: 352: 349: 346: 342: 338: 335: 332: 326: 323: 320: 316: 312: 309: 306: 295: 292: 278: 268: 266: 263: 262: 259: 256: 253: 245: 243: 240: 239: 237: 232: 229: 226: 222: 218: 215: 212: 182: 172: 170: 167: 166: 163: 160: 157: 149: 143: 139: 135: 130: 125: 124: 122: 117: 114: 111: 107: 103: 100: 97: 79: 76: 66: 65: 52:Find link tool 28: 26: 19: 13: 10: 9: 6: 4: 3: 2: 837: 826: 823: 821: 818: 817: 815: 804: 799: 797: 792: 790: 785: 784: 778: 776: 772: 768: 763: 760: 756: 751: 746: 743: 742: 738: 729: 725: 720: 715: 711: 707: 703: 696: 693: 688: 681: 674: 671: 666: 662: 655: 652: 647: 640: 633: 630: 623: 621: 606: 603: 578: 575: 566: 560: 551: 524: 517: 514: 511: 494: 491: 484: 478: 475: 471: 468: 465: 461: 458: 444: 438: 429: 424: 414: 411: 404: 397: 394: 385: 379: 373: 370: 356: 350: 344: 336: 330: 324: 318: 310: 304: 293: 291: 264: 257: 254: 251: 241: 235: 230: 224: 216: 210: 202: 200: 199:weak sampling 195: 168: 161: 158: 155: 137: 128: 120: 115: 109: 101: 95: 87: 85: 77: 75: 72: 62: 53: 48: 43: 39: 38: 34: 29:This article 27: 23: 18: 17: 775:expanding it 764: 749: 709: 705: 695: 686: 673: 665:ResearchGate 664: 654: 645: 632: 552: 297: 203: 198: 196: 88: 83: 81: 70: 69: 59:January 2021 56: 30: 659:Hsu, Anne. 531:, otherwise 271:, otherwise 175:, otherwise 814:Categories 767:statistics 624:References 508:, if  248:, if  152:, if  50:; try the 37:link to it 637:Xu, Fei. 515:∈ 472:∈ 454:∑ 366:∑ 255:∈ 159:∈ 40:. Please 728:22141440 607:′ 579:′ 495:′ 479:′ 462:′ 415:′ 398:′ 374:′ 726:  33:orphan 31:is an 765:This 683:(PDF) 642:(PDF) 771:stub 724:PMID 714:doi 646:MIT 197:In 82:In 816:: 722:. 710:36 708:. 704:. 685:. 663:. 644:. 802:e 795:t 788:v 777:. 730:. 716:: 689:. 667:. 604:h 583:) 576:h 571:| 567:x 564:( 561:P 525:0 518:h 512:x 499:) 492:h 488:( 485:P 476:h 469:x 466:: 459:h 448:) 445:h 442:( 439:P 430:{ 425:= 419:) 412:h 408:( 405:P 402:) 395:h 390:| 386:x 383:( 380:P 371:h 360:) 357:h 354:( 351:P 348:) 345:h 341:| 337:x 334:( 331:P 325:= 322:) 319:x 315:| 311:h 308:( 305:P 265:0 258:h 252:x 242:1 236:{ 231:= 228:) 225:h 221:| 217:x 214:( 211:P 169:0 162:h 156:x 142:| 138:h 134:| 129:1 121:{ 116:= 113:) 110:h 106:| 102:x 99:( 96:P 61:) 57:(

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"Bayesian word learning Sensitivity to sampling in Bayesian word learning"
"Sampling assumptions in language learning 1 Running head: SAMPLING ASSUMPTIONS IN LANGUAGE LEARNING Sampling assumptions affect use of indirect negative evidence in language learning"
"Lecture 20: Strong vs weak sampling"
"Sampling assumptions in inductive generalization"
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10.1111/j.1551-6709.2011.01212.x
PMID
22141440
Lecture 20: Strong vs weak sampling
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Sampling (statistics)
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